I led the team that developed Account Intelligence Agent. It was a cross-team collaborative effort, and we had to get many things right. Here is what we learned about building AI Agents.

Cross post from LinkedIn.

Fall in love with the problem that agents are best suited to solve: Account Intelligence is a critical component that sellers gather, research, and validate about their customers. It reflects the customer’s story, and the context is essential to understanding how to solve their needs with your product.

The real problem? Building account intelligence, especially for small businesses with limited public data, is challenging. It can take hours to perform the research manually. Multiply by thousands of such prospects - it becomes painful enough to sustain. Automation can only get canned intelligence riddled with gaps.

We believed this was a significant problem that Agents could solve more efficiently than existing methods. Avoid problems that can be solved by other means, like automation, or where there isn’t an agent-problem fit.

Leverage the best tools: Building your own foundational capabilities like LLM or Trust layer from scratch is a trap - you’ll spend months while the field evolves past you. By the time you’ve built your own framework, it is already outdated.

We built the agents in Agentforce Platform. We set up zero-copy integration, built RAG retrievers from unified data in Data Model Objects in Data 360, and leveraged the Agentforce Observability feature, which provided a pulse check on functional and non-functional metrics. It gave us the confidence that we are building a secure, scalable, and maintainable agent.

Architect for rapid evolution: The architecture should support portability and configuration. Swapping LLM models, changing retrieval parameters, moving between instances, and sharing tools should be possible without major rework or deployments. This enables rapid iteration and experimentation.

With new features, models, techniques, and patterns introduced in the Industry, it is essential that the design support modularity to swap components in and out.

Form a small Cross-Functional Team with strong collaboration and enable shared learning: Traditional Agile, tied to strict ceremonies, self-organizing, and established processes, is workable for general software development but not for Agent development.

For one, it takes a cross-functional org - business, product, domain, software, solution, data, and delivery experts - to get the agent right. Unless your team is like the one above, dependencies can cause disconnects and delays. The best way to shorten the feedback loop is to have all your subject matter experts collaborate.

Our cross-functional team had experts from different organizations. We were well connected horizontally (between teams) and vertically (between leaderships).

Iterate Rapidly: Each day, we would spike on tens of experiments to fail forward. There is a learning in each experiment that we would feed forward to the next one. We were outcome-driven since day one - every experiment and variant generates an account intelligence artifact that is comparable to a benchmark.

We would validate with our power users, gather their feedback, and iterate. Every day, the global team would convene to share what they learned from their experiments and brainstorm for the best outcome.

Challenge every hypothesis: At the beginning, we had data indicating that users may not wait 2-3 minutes for the agent to generate the intelligence. We introduced pre-processing to show what a great Account Intelligence report looks like, and then adjusted to asynchronous processing.

The users received their intelligence reports quickly on pre-processed prospects and customers, but were willing to wait for the artifact delivered via Slack. Trying to improve performance prematurely would have come at the expense of accuracy.

What are the lessons you learned in your journey? Share it in the comment section!

#agentforce #salsforce #agents #agent-development #lessons

So, I needed a car for the day. I used a major rental car provider’s website to book a car as my past experiences with the rental company were good. I filled out the online reservation and submitted it. It gave an error and asked to try again after a few minutes. I did and it errored again. In the third try, I changed the pickup time and location and tried again. It worked.

Done right? I was wrong. When I checked my email, I found I had three rental confirmations and a triple charge on my credit card. I thought to myself - oh no, not the red phone fiasco again.

I tried to cancel online and it promptly applied a cancel fee. Then, I created a ticket with the company giving them specific details on which ones to cancel. Someone responded that I must call them to cancel. I called them the next day and a few robot prompts later, I was able to speak to a human. After I explained the situation, they verified the reservation and cancelled the other two.

Why did I end up with three reservations? When I tried the first two times, it looked like the system had crashed. A “Unknown error” popped up, asking me to retry. But behind the scenes, the story was different. The system had actually finished the reservation successfully. The only thing that failed was the post to the confirmation screen—the system just didn’t respond with “Success” fast enough, so it timed out making the front end think something went wrong in the backend.

Can this be fixed in the Agentic Universe?

I have developed a nasty habit of projecting every current system problem into the agentic world. Given that the tech industry is obsessed with “agents,” would it solve for the end user? Sure, enterprises are building agents to capture new markets, increase productivity, and reduce costs, but what is the value transfer to end users?

First, lets see what the experience should look like. The booking experience could have been better. Here is what Brian Chesky’s Experience Rating levels (used to be 7 stars and now it is 11 stars) would have looked like for this scenario:

3 Star Experience: You visit the website, select dates, filter for “SUV”, manually enter your name, address, and credit card number. You hit submit. It books the car. This is the standard web 2.0 flow.

5 Star Experience: You open the rental app. You give minimal information and use Face ID to pay. Confirmed in 10 seconds. The backend is still shared so the issues with 3-star are still there.

7 Star Experience (The Agentic Experience): You just tell your AI, “I’m going to Miami.” It knows you need a car. It asks few details and preferences for you, and simply pings you: “I have booked a car for you.” You break free from rigid experiences.

9 Star Experience (The Personalized Agentic Experience): Your personal agent assists you in booking a car. It takes your booking by voice. The agent just confirms your preferences and seeks approval. It lets you customize the booking, watch for deals, and make changes on the fly.

11 Star Experience (The pseudo* AGI Experience): You don’t even ask. Your AI notices you booked a flight yesterday, checks your loyalty status, and puts a hold on your preferred car. It knows you disembark at Miami but fly out from Fort Lauderdale, so customizes the pickup and drop location that is closer to you. When you disembark, you get a notification that the rental car is ready for pickup.

*psuedo AGI - I personally think AGI is a long way. So until then the best bet is to mimic.

The reality

We are still stuck in a 3-star world - broken processes, complex interfaces, too many human interventions - when we believe we have the technology for 7/9/11-star agentic experiences.

Unfortunately, we will be stuck for a while. Companies have spent decades building their current processes, apps, and operations. The path forward for them is not about starting fresh - it’s about working around their legacy debts. That’s why most AI agents today feel more like fancy chatbots than actual enablers.

In this whole episode, I was involved in three different experiences - the UI experience with reservations, then with the case support, and finally with the phone support. I spent around 3 hours including context switches.

Current World Process Map

The existing processes are designed for human ←→ system transactions. When systems are involved, the transactions are not agentic; they are 100% programmed and deterministic between systems and humans. Then, when you add an agent to the mix, they struggle to work around the old world inefficiencies and gaps.

This diagram captures the core challenge of Human-Computer Interaction - a discord between how humans naturally think and how computers actually work. On one side, humans are unpredictable and independent – we solve problems creatively, change our minds, make typos, and jump between tasks based on intuition and context. On the other side, computers follow strict rules, producing the same output for the same input every time, unable to deviate from their programming or interpret what you probably meant.

When these two different behaviors meet, frustration emerges in both directions. Humans experience computers as rigid because the system won’t bend to accommodate natural human behavior like spelling mistakes, vague requests, or doing things out of order. Meanwhile, computers make humans feel limited because to get anything done, we must abandon our natural thinking and conform to the machine’s logic through specific menus, required fields, and fixed workflows.

This is known as the Gulf of Execution – the gap between how we want to accomplish something and how the computer demands we accomplish it. In essence, humans are creative and flexible while computers are orderly and inflexible, and when they interact, we feel constrained and the technology feels broken

The system barely has context outside of the transaction. It doesn’t know if you are booking a car for yourself or your family or if your previous booking failed. The second and third transactions also booked the car for me. The system thought I was renting three cars, all at the same time in two different locations. It is plausible but not probable. If I had called the company, they would have been able to book it in a single transaction and would have raised a doubt about the need for other two bookings.

Recall that I had to deal with three different experiences - the UI for reservations, then with the case support, and finally with the phone support. The failure of each experience led to the next with a changed goal. I started with wanting a cheap deal and ended up with a refund with no fines.

Could an agent (on the company’s side) overcome this? Let’s look into how most enterprises are ‘agentifying’ their processes. Agents are bolted on top of the old world and tools are strangled or embedded within the existing apps.

The agents attempt to bridge these disconnected systems but don’t replace or modernize them, creating additional layers of complexity rather than simplification. The friction intensifies through conflicting policies shown on the right: users must call to cancel without charges (forcing them from digital channels to voice), and cancellations are only free when it’s the company’s fault – a subjective determination that AI struggles with. This creates a classic “Deflection vs. Resolution” problem where the company deploys multiple agents to automate and deflect volume, but because these are superficial additions rather than systemic improvements, bureaucratic policies and complex rules that bots can’t handle force customers back toward human agents anyway, resulting in a high-effort, frustrating loop that satisfies no one.

Agent Native solution

Imagine a rental startup that decided to build an AI Agent native solution from scratch.

In an agent-native architecture, a single Experience Agent would own the entire customer journey, mimicking a walk-in rental office experience. When you walk into a physical location and the first booking attempt fails, the sales representative doesn’t make you start over with someone else – they own the retry, they know you’re booking just one car, and they prevent duplicate charges because they have the full context.

An AI agent can absolutely replicate this accountability. When a booking fails, the Experience Agent wouldn’t punt to another channel or make the customer repeat themselves. It would own the retry with full context of what just happened. Through intelligent choreography, it could delegate specific tasks behind the scenes – a troubleshooting sub-agent could verify if the transaction actually went through despite the error message, a payment sub-agent could reverse any duplicate charges, and a booking sub-agent could complete the retry – all invisible to the customer. The Experience Agent maintains the conversation thread, the context, and most importantly, the accountability for resolution.

This isn’t about having fewer agents; it’s about building an agentic enterprise where an agent takes ownership while orchestrating specialized capabilities as needed, creating a truly seamless experience where the customer feels heard, understood, and taken care of – just like walking into that rental office where one person helps you from start to finish. There are no alternative rigid UI experiences at all.

Closing Thoughts

Despite all the years of digital transformation, most customer experiences are still fragmented by disconnected workflows, fuzzy policies, siloed data, and incompatible tools. When breakdowns occur, the customer often becomes responsible for responding and following up. This leads to repeated form fills, redundant explanations, navigating multiple interfaces, and reliance on someone with proper authority to handle problems the system cannot resolve.

The bolted AI agents don’t solve these. When integrated into the current system, they face the same challenges: no context, no authority, ambiguous policies, and no transition. Rather than making the experience better, they expedite the process leading to deadlocks. Chatbots, in particular, take the lead in not being able to handle issues. And worse, automation cuts costs but at the expense of increasing customer frustration.

The value of agentic systems lies in ownership, not just better interfaces or quicker transactions. An agent-led organization restores to fragmented processes what it lacks: a single entity that takes responsibility, truly knows the customer, brings continuity when something goes wrong, and sees it through to resolution. This approach does not demand system replacement overnight but rather a shift in accountability from individual processes to the customers’ experience.

If companies neglect to prioritize agent accountability in their design, customer experiences will remain mediocre regardless of technological developments. Achieving excellent service requires fewer excuses, clearer ownership, and systems that respond to people, rather than increasing the number of agents.

With this shift, I hope booking a car will no longer feel like interacting with software, but rather like receiving authentic help.

Several years ago, in the company I worked for, their password policy was a hassle; They said: “Change your password every few months”. It was a multi-step process - Update credential stores. Then Log in and out of devices. Repeat for Mobile Phones. It was annoying, but manageable.

Then came passphrases. The promise: a stronger password you could keep for an year. I jumped in.

The old problem was solved. The new problem? Manually typing a 30-character, error-prone passphrase multiple times a day. We simply traded one hassle for another.

This is the trap of first-order thinking. We see the immediate fix (no more resets) but ignore the “and then what?” (daily typing hell).

The antidote is second-order thinking. You must look past the immediate solution to anticipate the consequences that come after the fix. The goal isn’t just to solve Problem A. It’s to ensure Problem B—the one you just created—is a better one to have.

We win the trade when the new solution meets these criteria.

1. The New Pain Must Be Smaller

A solution fails if its new problems are more painful than the old ones.

My passphrase trade was bad. The daily friction wasn’t worth the small gain. A real solution, like a FIDO passkey or biometric ID, solves the original security problem while creating a tiny new problem (a one-time setup).

If the “fix” just creates a different, equal-sized headache, you haven’t made progress. You’ve just rearranged the furniture.

2. The New Value Must Be Transformative

Sometimes, a solution is so valuable it justifies its significant new problems.

The automobile “solved” slow, limited travel. In exchange, it gave us traffic congestion, pollution, and fatal accidents. But the value it unlocked—personal freedom, modern logistics, and sprawling economic growth—was so immense that we accepted the trade.

Today, Generative AI is solving massive problems in code, content, and data. The new problems it creates—ethical concerns, factual hallucinations, and massive job market shifts—are enormous. But the potential value is so transformative, we’re collectively deciding these new, complex problems are worth taking on.

3. The New Access Must Be Democratized

Look at cloud computing. A decade ago, launching a tech company required massive capital for servers, data centers, and IT staff. This barrier to entry was the problem.

Cloud platforms (IaaS, PaaS, SaaS) solved this. They gave a startup the same power as a global enterprise for a tiny cost.

Does the cloud create new problems? Of course. It’s a maze of service complexity and adds new responsibilities for developers. But these problems are vastly preferable to the old one: not being able to compete at all.

The ‘Solution Pre-Mortem’

Stop asking, “Does this solve our problem?” It’s the wrong question.

Before you ship, make your team answer two questions:

1. What new problems will this solution create? (Name them. Be specific.)

2. Are these better problems to have?

This is the difference between simply reacting and building with purpose.

Keep building.

It takes 10 years to become an overnight success. Along with this, it also takes a lot of discipline. The stories of prodigies and successful people highlight that the path to success is a lot convoluted, and it needs us to keep on track and keep the north star in sight.

Regardless of where you are in your journey, ask yourselves the following questions.

Yearly Questions:

Are you happy now?

What do you want to have?

What do you want to let go of?

What will you do this and next year?

What do you want to be in 5 years?

What do you want to be a decade later?

Are you spending your time and energy in __________ ?

Daily Questions:

What am I going to accomplish today?

A better way would be future phrase it. Before the end of the day, I would have done __________

What will I do today to get closer to my yearly goal?

What will I do today to get closer to my 5-year goal?

What will I do today to get closer to my 10-year goal?

What is helping me? Continue.

What is not helping me? Stop.

Spell it out! It helps.

Writing your thoughts may give you better clarity and organizing. Often, we only have an abstract representation of our desires. When you have it in writing, it removes the ambiguity, and also it can help you set the scope.

I was keeping all my goals or desires in my head as though it was a secret. Not only, I had the luxury to change it often but also I could stash it when I failed as though nothing happened. So, when you can, let the folks know about your goal and recruit them as mentors, cheerleaders, or champions. You will feel accountable and commit to yourself. Not only that, with your folks knowing, you get automatic reminders. :)

The farther the time ahead, the greater should be your goal.

Set your immediate or near-term goals achievable. At the same time, raise your bar really high for the long term. Let’s say you want to be an author or you want a career in literature then getting a Nobel prize in Literature is not a near-time goal. I want to finish writing 100 pages is a reasonable near-term and winning Nobel Prize can be a long-term goal.

Align your 5-year and 10-year goals to a common theme. So, considering the earlier example, you may want to align your 5-year inline with your 10-year goal.

Every day matters.

Good Luck! Start your list and pursue your goals.

Creativity disrupts the mundane. But what disrupts creativity?

We are all creative, but we often struggle to produce meaningful work. The path forward feels vague, and it’s easy to get stuck.

Understanding the barriers that block our output is the first step to overcoming them.

1. The “All or Nothing” Trap

We want to do everything, so we push the deadline. Scope creep leads to a never-ending list of additions until, overwhelmed, we give up. We are left with nothing.

Consider Brandon Stanton of Humans of New York (HONY). Stanton’s journey offers a key takeaway:

“If you feel stuck, stop dwelling on the big picture... Instead of focusing on the life arc, focus on one step at a time.”

The solution is to get the first version out. Take one step, consistently.

2. The “Magnum Opus” Complex

We want to create a masterpiece that outlives us. In the pursuit of “our best work,” we add endless details until self-doubt paralyzes us.

Stanton again offers the antidote:

“People are paralyzed by the need to make something great... But my decision to do HONY was just a decision to work on what I loved every single day.”

Focus on the process, not the monument.

3. The “Lone Wolf” Burden

Fear and anxiety about the outcome make us want to work in secret. We go it alone. But isolation is a barrier. We need companions, mentors, and peers for support and valuable feedback.

4. The “Curse of Knowledge”

Expertise can be a trap. Knowing a subject deeply also means knowing all its constraints. We become uncomfortable thinking outside these boxes and trade breakthrough ideas for “practicality.”

True free-thinking requires capturing “crazy” ideas to connect the dots in new ways. The solution? Intentionally break free from your own constraints.

A New Partner: The Generative AI

These barriers are deeply human. But today, we have a new tool that fundamentally changes the equation: using Generative AI.

An LLM can act as a powerful co-pilot to smash these barriers:

• Beats the “All or Nothing” Trap: Paralyzed by a blank page? An LLM can generate that “crude first draft” in seconds. It instantly moves you from creation to refinement, giving you something to react to.

• Deflates the “Magnum Opus” Complex: Instead of agonizing over the “perfect” phrase, you can ask an LLM for ten variations. This lowers the stakes and makes iteration fast and objective.

• Solves the “Lone Wolf” Burden: An LLM is the ultimate 24/7 companion. It’s a tireless brainstorming partner, a feedback mechanism, and a mentor you can bounce ideas off without fear of judgment.

• Breaks the “Curse of Knowledge”: An LLM isn’t bound by your human constraints. Ask it to connect two completely unrelated topics. It’s a powerful tool for generating the “crazy” ideas needed to see beyond your own expertise.

The LLM isn’t the creator—you are. It’s a partner that handles the friction, allowing you to focus on the work only you can do.

But as a customer, my recent experience taught me a hard lesson: just having a Customer 360 strategy isn’t enough. Getting it right is critical.

The Story: A Simple Color Change

I switched my phone’s carriers. I placed an online order for three new phones but immediately realized my mistake: I had chosen red for all of them instead of black.

I figured a quick chat would fix it.

Strike 1: I used the chat feature. The rep couldn’t see the order in the system and told me to call back the next day. The next day, they still couldn’t pull my data.

Strike 2: Two days later, a rep finally saw the order. But to help, they needed a password. I never set one. The rep was confident I should have one, I was confident I hadn’t. We were at a standstill. They politely refused to help.

The “Deadlock”: I tried to reset the PIN online.

• To reset the PIN, I needed an account.

• To create an account, I needed my new phone number.

• To get my new phone number, I needed the phones... which hadn’t shipped.

I was trapped in a broken logic loop.

Strike 3: I asked if I could go to a physical store. “Yes,” they said. I went, showed my ID. The store rep could verify who I was but explained their system couldn’t access my web order to make a change. They also warned I wouldn’t be able to change the color once the phones arrived.

Helpless, I emailed the CEO. The ‘presidential services’ team got involved, and after several more emails, they finally resolved it by canceling the entire order, processing a return, and placing a new one.

All for a simple color change.

Where the Customer 360 Vision Broke Down

This experience was a perfect failure analysis of a system that looks good on paper but fails in practice.

• System Time Lags: My order was invisible for days. Different systems clearly had different information, and my old, abandoned quotes from the past seemed to be “muddying the waters” for the reps.

• Siloed Data & Tools: It was obvious that reps in different channels (chat, phone, store) were looking at different screens. The in-store rep had no access to my web order. The late-night rep (complete with roosters crowing in the background) had to escalate to a superior just to view my details.

• Inconsistent Knowledge: I got a different answer from every rep. “It’s an easy change.” “We’ll have to charge you a restocking fee.” “You have to cancel the whole order.” Only one person knew the correct (and final) “cancel and re-order” process.

• Asymmetric Trust: This was the most frustrating. The carrier had no problem using my SSN and personal data to run a credit check and charge my card. But to help me, I had to prove my identity with a PIN I was never given, with no other MFA options available. They trusted me to pay, but not to be helped.

• Process Deadlocks: I was trapped in a ‘catch-22’ built by their own processes. It was a completely broken, automated flow with no human override.

• Broken Channels: The web portal, my chosen channel, was missing crucial steps (like setting a PIN or an ‘edit’ button). The IVR’s callback feature was broken, echoing the last digit of my number in an endless loop. The customer journey was a black hole.

Takeaways for Leaders

First, the obvious: I should have double-checked my order. But mistakes happen. A good system should allow for simple fixes.

• Executives: Be your own customer. You must get first-hand experience of your product. Place an order. Try to get help. Test your security. You will never see this kind of pain in a dashboard metric.

• Empathy is not enough. Every rep was cordial and “empathetic.” But empathy without empowerment is useless. My goal was a color change, not a therapy session. The reps were just following a broken script.

• Actively hunt for deadlocks. My problem was an edge case, but it was one I couldn’t solve myself. Your automated processes must have a human override. Don’t automate your customers into a corner.

• Inconsistent tools create inconsistent experiences. If your in-store tool, web tool, and phone tool all work differently, you don’t have one company; you have three confusing ones.

• Get your trust framework right. If you make it easy for a customer to give you data (SSN, credit card), you must make it just as easy for them to prove who they are to get service. A single point of failure (a PIN I never set) is not a security policy; it’s a barrier.

It just shouldn’t have been this hard.

What about you? Have you ever been trapped in a “helpful” process gone wrong?

I learned a lot during the process.

Identify your needs by priority:

It’s easy to get caught up in the moment and lose sight of our personal goals and priorities. Identifying what you want is important because it helps you to clarify their values, preferences, and aspirations and to develop a clear plan for achieving their desired outcomes.

So make a list and rank them by priority:

1. Health/Lifestyle/Employment Status priorities

   1. I want to _____

   2. Then, I want to _____

2. Work priorities

   1. I want to be in _____ role

   2. I want to work in _____, _____ or_____

3. Financial Priorities

   1. I want to earn _____ more than _____

Interestingly, I used to think short-term and long-term goals are a continuum. Short-term is incremental in small order (1+ to 2X), whereas long-term goals could be of higher orders (10X or, if you are lucky, 100X).

Now I have a distinct set, and I try to allocate time and effort toward long-term goals daily.

Finish your Resume:

Updating your resume is an iterative process. And you may need to customize it before you apply for a specific position.

1. Gather information: Collect relevant work experience, education, skills, and accomplishments to include on your resume.

2. Information: Decide on a format that best showcases your strengths and experience. Some standard options include chronological with recent first, functional, and combination resumes.

3. Header: Include your name, email & phone, and relevant certifications or licenses at the top of the resume.

4. Summary: This should be a short summary of your skills and experience and highlight the value you can bring to a potential employer. You may need to customize it to highlight specific values for a given role.

5. List Work experience: Start with your most recent job and work backward. Include the company’s name, job title, and a brief overview of your key responsibilities and achievements.

6. List Education: Include any degrees or certifications you have obtained, along with the name of the institution and the field of study.

7. Include any relevant skills: These could include technical skills, language skills, or other relevant abilities. This could be a tag cloud or a matrix.

8. Review and edit: Carefully proofread your resume to ensure that it is error-free and easy to read. Consider asking a friend or colleague to review it as well. Alternatively, you can request a professional review. LinkedIn has professionals available for hire.

I prepared a master resume and trimmed it as needed. I also had it in an uploadable word document format and plain text format to copy and paste into Application forms.

Another important thing you need is to keep your public information up to date on social sites like LinkedIn.

Leverage your Network:

Throughout your career, you learn the skills to do the job. But you also earned the trust of your colleagues, many of whom would be ready to work with you in a heartbeat.

All your years of kindness, ability to work together as a team, and putting people first will work for you. So reach out to your colleagues and network - ask for references or positions that they know are available. I discovered the chances of getting an interview and the speed of interviewing process greatly improved when going through a referral.

Needless to say, my fantastic colleagues in my network have helped me achieve the best outcome.

Preparing for the Interview:

This needs some serious thinking. As an experienced person, you may already have the necessary job skills. But answering what the interviewer wants to hear from your personal work experience needs preparation. This, again, is an iterative process.

The good news is you can prepare a write-up that you can use effectively in your interview. Here is how:

There are many preparation methods, but I have found Amazon’s STAR method to be the most effective.

• SITUATION Describe the situation you were in or the task you needed to accomplish.

• TASK What goal were you working towards?

• ACTION Describe the actions you took to address the situation with an appropriate amount of detail and keep the focus on you.

• RESULT Describe the outcome of your actions, and don’t be shy about taking credit for your behavior.

  You can use the STAR method to highlight a behavioral principle. Again, Amazon’s Leadership principles come in handy. I created a table with all leadership principles, started writing stories from my work experience, and aligned them to the leadership principles. My recommendation is to have 10 to 15 STAR stories.

Tip: Copy the spreadsheet in CSV into your workbook and start writing your own STAR stories!

Once you have a stellar resume and documented STAR stories, practice well. Use your network and get referred to positions that align with your priorities. Shine in that interview!!

Good Luck!

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After a couple of visits in early 2020, during Pandemic - the Covid situation locked us all down. Not only venturing out was an issue, locked in closed spaces for hours without knowing who has been there or handled the items landed us in a tough spot. We decided to put a hold on 2020 or until the situation is more manageable.

But we didn’t have to wait. Last week, while I was in a meeting, my daughter sneaked in and wrote a quick note for me. The note asked if I wanted to visit her escape room. She had thought about our problem of not having an escape room experience since the lockdown; she decided to put one for us.

I agreed. Later that day, when my wife and I visited, we were stunned by the clues’ quality. The experience she had built for us was amazing.

Entry

We got an introduction. The goal was to find the dolphin pen drive. We should not use shortcuts or brute force trying to open random boxes, and we must solve them through the course of clues. She just handed us a welcome note.

First Clue - There is no clue.

We read and thanked her for the note. And we asked for the first clue or where to start.

My daughter smiled and said, “You already have it. Go back to the note”.

We had to scramble and assemble the bolded letters. It read, “flip sequin.” We found a sequin bag and flipped it to find another note. It said, “sunset chalk.” We had no idea what it meant except that there was a box full of chalks. We picked the one that matched sunset colors and emptied it, but there was nothing there.

Time to change the strategy. There was also a wall painting with a sunset in it. There was also a chalkboard canvas on top of it. Ah! There it was. We flipped both the canvases, and there was a blurry picture in one of them. And there were three sticky notes in the other. And there were numbers on them 2, 4, 6. Must be key to a number lock.

But. we had no idea what the blurry picture was, and we failed to get it right. Dead End!

We gave up and asked my daughter for a lifeline. She mentioned that the picture was a real closeup shot of something in the room. We checked again, and it was the carpet! We found another note beneath the carpet. There were three words - blue, pink, and yellow.

We noticed that the sticky note she gave before were those corresponding colors. Now what? My wife realized that there was a box with a number lock on it. It had three numbers. Bingo! May be the order of the words was the combination. We used it and opened the box.

There was another note inside the box! Arghh! It had a snowflake and a recycling sign on it? The note made absolutely no sense, so we used another lifeline - this time, we asked the coordinator for another clue.

We were told that the symbols were the title of a book. Snowflake and recycle? There was no book like that .:-) She had her own bookshelf, and we raided them. On careful study, we found there was a book titled Winter Turning. On the whiteboard, there was an alpha-numerical code.

This must be the toughest escape room ever! The clues were set in the maze of a small 12’x12’ room. We decrypted, and it had a number 144. This is easy. It must be a page in the book. On page 144, guess what? There was another note! It said the owl. There were two owly things: a box and a key chain. We went to the box and opened it, and the box said, “It is the wrong owl, try again!”. And the keychain’s back was cut open, and there was a key.

The key unlocks a diary. We opened it. The diary had a jumbled note of letters. We scrabbled and came up with a word - pillowcase.

Finally, we opened the pillowcase expecting another note, and there it was. It said - this was your last clue and a note that said:

Don’t go any farther, think inside the box

We looked for boxes in the room and there were several. We opened one after the other and finally, there was a dolphin pen drive.

Mission accomplished!