The Conductor, Not The Coder
Your job is changing faster than you think.
The job isn't about writing code anymore. It's about telling a junior AI developer exactly what code to write, and then checking its work.
Your Coding Output Just 3x'd, But You Wrote 90% Less Code
A developer's recent experience reveals the rapid shift from coder to AI conductor.
A developer's coding output recently tripled in three weeks, while the amount of code they personally wrote fell off a cliff. The secret is not a new framework, but a workflow where they act as a technical project manager, directing AI models to do the actual building. The job is no longer just writing code; it's orchestrating an AI that does.
This signals a fundamental change in the work itself. The most valuable skills are shifting from syntax fluency to system design and prompt engineering. It's about translating a complex problem into a series of clear, unambiguous instructions that an AI can execute, and then having the expertise to rigorously review the output.
This model turns senior developers into massive force multipliers, capable of prototyping and iterating at an unprecedented speed. If you're still just writing boilerplate, you're competing with a machine that does it for free. The real job is now conducting the AI orchestra.
Building the AI Scaffolding
With the magic trick of basic AI getting old, the industry is now building the serious plumbing required to make it reliable.
OpenLIT: Finally, see what your LLM is actually doing
OpenLIT provides zero-code observability for your LLM apps because running AI without it is like flying blind. This is the boring, essential infrastructure that moves AI from a cool demo to a real product.
RedPill: Cryptographic proof that your AI queries are private
RedPill offers provable privacy for AI queries, using secure hardware to ensure your data is never exposed. It’s for builders who realise 'trust us' is not a viable security model for enterprise customers.
Layercode CLI: The one-command wonder for voice AI agents
Layercode CLI abstracts away the nightmare of building global voice AI infrastructure into a single command. It’s another piece of scaffolding that lets developers focus on an agent's brain, not its plumbing.
AI Is Getting a Real Job
The next wave of AI tools aren't just chatbots; they're specialised agents designed to perform specific, high-value tasks.
Praxim for Word: AI that edits your Word docs without ruining them
Praxim is an AI agent that actually edits complex Word documents while respecting your existing formatting. This moves beyond generating text to intelligently manipulating it inside the tools you already use.
Lyra: The AI that turns chatter into action
Lyra turns meetings into live 'deal rooms' where the AI helps generate action items and update your CRM in real-time. It’s designed to produce outcomes, not just meeting notes that nobody ever reads.
Intryc: The AI coach your support team needs
Intryc uses AI to run customer support simulations, training agents on real tickets and scoring their performance. It's a targeted AI coach, not a generic knowledge base, built to improve a specific business metric.
Quick hits
Blai: Your AI crypto BFF that trades for you
This AI crypto advisor uses a 'chat to trade' interface, aiming to make complex investing feel as easy as sending a text.
Dad Reply v1.5: One-click email replies with 'dad energy'
A beautifully simple extension that replies to emails with a single emoji, because not every message needs a paragraph in response.
Androidify: Google let Gemini take the wheel
Androidify is back and uses Gemini to turn your selfies or text prompts into custom robot avatars, for better or worse.
My takeaway
The most valuable skill is no longer coding; it's translation.
We are all becoming translators between ambiguous human intent and literal machine execution. The better the translation, the better the result, whether you're prompting an image generator or directing a coding agent. This is the new bottleneck and the new source of leverage.
The challenge is that great translation requires deep domain knowledge, not just clever words. So, how do you cultivate the expertise needed to ask the right questions? What happens when your value is measured by the quality of your instructions, not the speed of your hands?
What does it mean for your career when your primary output isn't the work itself, but the instructions for the work?
Drop me a reply. Till next time, this is Louis, and you are reading Louis.log().