Prototype to Production

I built a working AI prototype that could process PDFs perfectly. Then I tried to move it into production.

That's when I discovered OpenAI's API handles PDF processing completely differently than ChatGPT does. The prototype worked great in the interface, but the API? Not so much.

Turns out PDF handling was only added to OpenAI's API last month – and it's still pretty limited on file sizes. My prototype hit those constraints immediately.

I pivoted to Claude's API, which handles PDFs up to around 30MB. Problem solved, but it got me thinking about a bigger issue - always validate API capabilities early, even when the UI version works flawlessly. What works in conversation doesn't always translate to production code.

This isn't the first time I've hit this kind of mismatch. The gap between demo and deployment can be surprisingly wide.

Two Types of "AI Agents" - And Why the Distinction Matters

Working on AI implementations, I keep running into confusion around the term "AI agent." Turns out we're talking about two completely different things.

Type 1: Autonomous AI Agents These are the systems getting all the buzz. An AI agent can perceive its environment, decide which tools to use, and execute actions without constant hand-holding. Think customer service bots that access your CRM, check inventory, process returns, and escalate issues - all while maintaining context and making smart decisions.

Type 2: AI-Enhanced Workflows
This is AI plugged into traditional automation platforms like Zapier, Make, Power Automate, ServiceNow, or custom solutions. The AI handles specific tasks within a larger, predictable process flow.

Real example I'm building: Staff scan shipping labels with a mobile app. AI extracts supplier info, model numbers, delivery dates, and populates our equipment database. Standard workflow automation then triggers notifications to procurement, project managers, and finance.

But here's where it gets interesting: The system also compares delivery timelines against project schedules. When procurement suggests equipment substitutions for cost savings, AI evaluates whether the new supplier's lead times will mess up critical milestones. If there's a conflict, it sends up an alert that can be acted upon.

The key difference: Workflows excel at consistent, repeatable processes. Autonomous agents shine when you need adaptive decision-making across multiple variables.

The most powerful implementations combine both - workflow automation for operational consistency, enhanced with AI agents for complex decisions.

In leveraging AI for business operations, getting this distinction right can save serious time and headaches during deployment.

What are you seeing out there? Are you building agents or workflows?

Stuck on Deployment

I built a nifty AI utility tool for a client that will look into a google folder and sub folders, ingest all documents, then extract names & titles of all the people it finds inside. It’s a quick way for the sales team to comb through historical contracts, SOWs, project plans, etc and find the people we’ve worked with in the past who could become new contacts – even if they’re at new companies.

Scripting the AI prompt took a couple of hours. I needed a tight prompt so the end user doesn’t have to interact with the script yet still receives a tidy output list every time. That turned out to be the easy part.

For this project, the challenge (for me) was the deployment, especially as I learned more about Google’s ecosystem. Linking Apps Scripts to a GCP project, enabling Google Drive API in Cloud Console and adding it to the Apps Script, authorizing the script, etc. The deployment took many more hours than the AI piece. I felt frustrated – right on the verge of having a useful tool, but stuck in the details of deployment.

I eventually set it aside for the night and came back the next morning. I asked AI to create a checklist of EVERY SINGLE detail necessary for setup and deployment. That cracked the case and got me across the finish line.

Using AI to solve the deployment issue was pretty nifty as well.

Thoughts on Prompt Engineering

Prompt engineering is an art form – and it’s already a legitimate career path, even if many companies haven’t caught up yet.

As LLMs get more powerful and can handle longer reasoning sessions (we’re talking 10+ minute processing times now), a well-crafted prompt becomes the difference between impressive demos and reliable, production-ready automation.

Sure, anyone can get cool results from conversational agents. But building prompts that deliver consistent, predictable outcomes for business-critical tasks? That requires genuine skill, experience, and strategic thinking.

I’ve seen teams spend multiple hours perfecting a single prompt – and save hundreds of hours downstream. Every word matters. Every sequence matters.

My approach? Treat prompt writing like crafting a compelling essay. Structure, flow, and precision all count.

Here are three game-changing techniques I’ve learned:

Examples are gold. Sometimes showing beats telling by a mile – even for AI. One solid example can communicate what paragraphs of instructions can’t.

Order is everything. The sequence of your instructions dramatically impacts results. Pro tip: put your most critical requirements at the end – that’s what the model “remembers” best.

Test relentlessly. Great prompts emerge through iteration, not inspiration. Build, test, refine, repeat.

There are fantastic tutorials out there (easy to find, though mastery takes practice), and tools like Promptmetheus or Originality can accelerate your workflow. But I’d recommend starting with manual practice first – understanding the fundamentals makes you a better prompt engineer long-term.

How’s your prompt engineering journey going? Are you seeing it become more important in your work too?

Framework for Finding ROI from AI

The highest value AI agents often aren’t the flashiest ones, but rather those that eliminate friction in existing processes.

I’ve had clients come to the table with ideas of things to build, but 50% of the time it’s not the most valuable agent for their business. How do you find the highest ROI?

My framework: MAP → IDENTIFY → PRIORITIZE → BUILD

Map: Start by building a customer journey map on Figma. Get the high-level view first, then drill into the details.

Identify: Look for repetitive, time-consuming steps with heavy text or voice components. With voice agents expanding rapidly, audio touchpoints are prime opportunities.

Prioritize: Focus on friction points that impact the most customers or consume the most resources.

Build: The cost to run an AI agent is negligible compared to development cost, so start with your highest-impact opportunity.

Real example: A SaaS company wanted a complex lead scoring agent. But mapping their journey revealed the real bottleneck was customer onboarding. A simple FAQ agent reduced their support tickets by 40% and freed up their team to focus on strategic accounts.

By starting with the customer journey instead of the technology, you’re more likely to land on solutions that drive real value. The opportunities we find this way are usually easier to build AND deliver higher returns.

Prompt Learning

Writing the prompt can be so much more than a line-by-line conversation with Claude or ChatGPT. Emerging research suggests there are ways to vastly increase accuracy. Things like describing its role, assigning a clear task, with specific rules, providing context, examples, and supplemental notes, can all improve the results. This is what makes low-code and no-code systems run with repeatability without hallucination. It takes time to build a first-class prompt, but the payoff is reliability and accuracy.

Here is a prompt I wrote asking Claude to create a Chrome extension for a password manager, storing my files in a local database. (I actually like Chrome’s native pw manager, but wanted to see if I could build an extension this way.) I tried this prompt in ChapGPT as well, but the experience was better with Claude. Copy/paste and watch what happens!

#Role
You are a web developer with a talent for Chrome extensions and JavaScript. You understand browser security and UI/UX design principles.

#Task
Create a personal password manager as a Chrome extension that safely stores passwords locally and helps me automatically save and fill credentials for websites I visit.

#Specifics
Detect login forms on webpages automatically
Prompt to save credentials after I’ve filled in both fields and attempt to log in
Prompt to autofill saved credentials when I return to sites
The save/retrieve prompt should stay visible for at least 8 seconds
Local encryption of all password data
Ability to export/import password data for backup
Clean, intuitive UI for managing all saved passwords

#Context
I currently use a third party password manager but want something I control myself for added security. I’m concerned about storing passwords in third-party services, even when they claim to use encryption. I need this to work with standard login forms and prefer simplicity over complex features.

#Examples
##Example 1
When I visit a site like twitter.com and enter my username/password, after I click “Log in” or press Enter, your extension should show a prompt asking if I want to save those credentials. The prompt should stay visible long enough for me to make a decision (at least 8 seconds).
##Example 2
When I return to a site where I’ve saved credentials, as soon as I click on the username field, your extension should prompt me asking if I want to fill in my saved credentials. If I click “Yes,” it should automatically fill both the username and password fields.

#Notes
– I’m comfortable with technical details but prefer code that’s well-commented and organized
– Security is my primary concern – all passwords should be encrypted locally with a master password
– The extension should work on most standard websites
– Keep the UI clean and straightforward
– I want to be able to view, edit, and delete my saved passwords through the extension
– Must work with Chrome

It Ain’t Sexy

It ain’t sexy, but it’s practical. I asked AI to write a bit of code to ingest a data file, parse and post the data to another database. The parsing rules are complex with many exceptions, which is why we’ve been doing it manually for years with an admin person.

A few hours to carefully construct the prompt, then maybe 5-6 hours testing and debugging; now it’s automated and saving up to 5 hours/week!

AI enabled this. Creating space for the human to do more high-value thinking.

What do I do? Selected highlights from Blue Fractal’s work in 2024

Companies/Industries Served:

·      Professional Engineering Services

·      Healthcare Tech Startup

·      Marketing Agency

·      Property Management for Affordable Housing

·      Design Software for the Construction Industry

A selection of work I did to help clients:

KPIs and Data

·      Instrument the business to establish baseline KPIs, begin measuring, and leverage data for decision making.

·      Calculate project profitability.

·      Root cause analysis for poor performing projects.

·      Develop and implement accountability standards for team members. Coach project leaders how to hold their teams accountable.

Business Operations

·      Install a cadence for the leadership team – quarterly planning with execution details and weekly checkpoints.

·      Streamline proposal writing process with standardized templates.

·      Financial systems migration from QB Desktop to QB Online.

·      Process improvements to streamline or automate work.

Product and Go To Market

·      Opportunity sizing for metal building manufacturer software.

·      Competitive landscape analysis for bringing offshore software solutions into the U.S. market.

·      Written phased requirements for software development roadmap and resource planning.

·      Authored business plan to inform go/no-go decision.

HR and Culture

·      Facilitator for employee communications workshop.

·      Change management workshop for leaders and managers.

·      Extract core values from leadership; proliferate company-wide through multiple channels.

·      Update and stimulate the employee review process.

·      Recruit and interview candidates for skills, experience and culture fit.

·      Create onboarding programs for new hires.

Marketing & Sales

·      From-scratch marketing literature and website content to move into new market segments.

·      Hands-on project management to create and execute marketing strategy.

·      Create a sales team commission structure.

Taking Action

I used to think, if I wanted to start something new, that I need a “big idea” to make it worthwhile and increase the chances that it will be successful. Most of us will not conceive a lottery-winning “big idea”. And even if we did, there’s really no increased chance of success just because of that. The idea still needs to be implemented and that could mean talking to people, getting funding, building skills, i.e. doing stuff.

Taking action is what makes the difference, even with small ideas. Everyone can come up with many small ideas. I may not be clear what the total future potential of the idea is, but I can take action on it now, see where it goes, and then evolve. Success is a process.

Training Will Set You Free

Have you ever hired a new employee, and after assigning them a deluge of tasks you start struggling to come up with new things for them to do? Often, it can take as much if not more time handing off tasks than it would have been to just complete the task on your own. Instead of managing new hires through tasks, manage them through a training program. Start small. If you don’t have a training program, have the employee build it as they complete their tasks. Ask to review their documents and course correct. They’ll develop a sense of ownership and the time you spend with them is leveraged beyond the task itself. Once you show someone exactly how to do something, and you are confident that they know how to do it, then you can stop assigning tasks and rely on them to do the job.

What is a Fractional COO?

I've begun working with multiple businesses as a fractional COO. This is a new space and many seasoned executives are looking at it, trying to figure out how to make it work. But what is a fractional COO? There seem to be a lot of different answers. Here is my vision and definition.

Just like a full-time COO, a fractional COO (fCOO) acts as a strategic partner with the business owner. The job of the fCOO is to enhance existing leadership into a team that can run the day-to-day without the the business owner’s constant intervention. The fCOO drives execution of the owner's vision with the leadership team (and, by extension, the rest of the company).

The fCOO is the leader of the leadership team. This is not an outside consultant; the fCOO is part of the org structure and the leadership team reports to him or her, even in a fractional engagement. The fCOO ensures that all of the various functions and departments of the business are integrated with one another and that everyone is rowing in the same direction.

In contrast, the VP of Ops/General Manager is a member of the leadership team who reports to the fCOO. They are responsible for the actual product or service that the business provides to its customers.

One reason for confusion between the fCOO and the VP of Ops/GM roles is that in the majority of businesses where the COO is full-time, he or she also serves as the organization’s VP of Ops/GM. Eighty percent of the full-time COO role is managing the day-to-day business operations, and 20% of the role is strategic development of the owner's vision.

The fCOO focuses on the strategic 20%. That's why it's fractional (not full time). The fCOO may perform this service for multiple companies at the same time.

For most operations teams led by a VP of Ops/General Manager, the 20% strategic work often get consumed in the whirlwind of day-to-day business. Client issues always take priority, and the company makes slow or no progress toward the business owner’s strategic goals. (This is often true even when a company has a full time COO.)

Having a fCOO focused on the strategic 20% improves the likelihood that the business will make crucial changes and improvements to achieve the owner’s strategic vision. That’s not to say there aren’t trade-offs with a fCOO operations leader, but if everyone understands where the fCOO is focused - on strategic activities (without disrupting the day-to-day business) - the fCOO model can become highly effective.