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Your AI agent is only as useful as the documents it can actually read.
Most AI demos start with clean Markdown.
Real businesses do not.
The important context is usually trapped in PDFs, Word files, spreadsheets, slide decks, scans and old client documents.
That is where many agent workflows quietly fail.
The model is capable.
The prompt is fine.
But the system never received the information in a format it could reliably use.
Firecrawl recently released two open-source tools that solve part of this problem:
• pdf-inspector identifies whether a PDF page is text-based or scanned, then routes it to the right extraction method.
• AnyDoc converts 14 common document formats, including Word files, Excel sheets, PowerPoint decks, EPUBs and CSVs, into clean Markdown.
That sounds like plumbing.
But it is actually one of the biggest differences between an AI demo and a useful business workflow.
Before asking an agent to reason about a client, project or process, make sure it can access the source material properly.
Better prompts are useful.
Reliable context is more important.
Firecrawl’s announcement: https://lnkd.in/eJaTh3TH
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Most AI teams are overcomplicating agents before they have defined the work.
I keep seeing architecture diagrams with five or ten agents talking to each other.
Research agent. Planning agent. Writing agent. Review agent. Manager agent.
But before adding another agent, I would ask a simpler question:
What is the actual capability we need?
For example, “quote generator” is not an AI agent strategy.
It is a capability with clear boundaries:
• It receives project requirements
• It can access approved pricing data
• It creates a structured draft
• It flags missing information
• A human approves it before anything reaches the client
That is easier to test, replace, audit and improve.
The useful shift in AI is not building a swarm of AI personas.
It is designing small, reliable capabilities with clear inputs, controlled access and a defined point where a person takes over.
That is how agentic systems become useful in real businesses, rather than another complicated demo.
Before adding the next agent to your workflow, map the work first.
What does it need to do, what can it access, and what should it never decide alone?
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Most AI tools give you answers.
Strawberry helped me do the browser work around the answer.
This week I used it to research viral content formats, turn the research into detailed Google Flow prompts, and build a repeatable content workflow.
The useful part was not getting another summary.
It was keeping the tabs, the research, the files and the next actions in one place.
Instead of copying context between a chat window, browser tabs, documents and tools, I could give the Companion an outcome and let it work through the browser workflow with me.
That is what makes it feel different from using AI as a standalone chat tool.
It is early, but I think this is much closer to how AI should fit into real work.
Try stawbeyy here:
https://lnkd.in/e_HMbkSy
#AI #Automation
Strawberry
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Everyone thinks AI coding agents need better prompts.
They don’t.
They need better memory.
A developer agent can write decent code in seconds.
But give it a real product repo and it usually hits the same wall:
It doesn’t know why decisions were made.
It doesn’t know which workflow matters most.
It doesn’t know what changed last week.
So it starts guessing.
That is why OpenWiki caught my attention.
It is an open-source CLI that turns a codebase into a self-maintaining, agent-readable wiki.
Not another prompt library.
A system for giving the agent context that can stay current as the product changes.
That is the shift I think more teams need to make:
Stop asking, “What prompt should we write?”
Start asking, “What does the agent need to know to make the next correct decision?”
The repo has already reached 15K+ GitHub stars since launching in June.
The tool is interesting.
The bigger idea is more important.
AI agents do not need more instructions.
They need a source of truth.
GitHub: https://lnkd.in/epcfUpTP
What are you using to stop your coding agents from guessing?
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I would like to thank Code Institute for providing me a great opportunity to enhance my web development skills.
#webdevelopment #softwareskills #codeinstitute
