AI Agents Enter the Mainstream: From Coding Assistants to Autonomous Workflows
The Agent Revolution Is Here
Today's AI landscape reveals a community grappling with the rapid maturation of coding agents. The conversation has shifted from "will AI replace developers?" to "how do we work effectively alongside autonomous agents?"
Best Practices for Agent-Assisted Development
Several prominent developers shared their workflows for maximizing agent productivity:
- Jon Kaplan advocates for always starting with Plan Mode, iterating in natural language before execution, and leveraging AI for code review
- Michael Truell (Cursor) recommends test-driven development as the feedback loop, reverting when things go sideways, and running multiple agents in parallel via git worktrees
- Eric Zakariasson emphasizes "plan sync, implement async" - aligning on plans quickly before handing off to cloud agents, and creating validation environments for self-checking
The Rise of Autonomous Loops
The "Ralph" pattern continues gaining traction - autonomous task processing loops that work while developers sleep. As one developer noted: "last night, I had a half-finished workflow and no energy to keep going. So I started Ralph, closed my laptop, and went to bed. This morning, 6 updates. Everything working."However, not everyone is convinced. Steve Krouse offered a contrarian take: "Managing lots of Claude Codes is super dumb... You're alienated from the work. Your feedback loops are terrible." He argues for being a "craftsperson with a powerful tool" rather than a manager of AI workers.
Infrastructure Developments
- GitHub Copilot now supports OpenCode's open-source agent without additional licensing
- Ollama gained compatibility with Anthropic's Messages API, enabling Claude Code workflows with open-source models running locally
- Remotion launched Agent Skills for video creation via Claude Code
- X open-sourced its algorithm, prompting immediate analysis from AI tools
The Human Cost
A poignant thread from Sofía López resonated widely: "I work in AI and I'm scared." The accompanying article discusses burnout among early adopters who struggle to keep pace. Another developer observed someone at 3am running their "tenth parallel agent session" and wondered: "in that moment I don't see productivity. I see someone who might need to step away from the machine for a bit."The Bigger Picture
Addy Osmani provided historical context through Jevons Paradox: every time we've made software easier to write, we've written exponentially more of it. The shift isn't about replacement but about "what orders of magnitude increase in knowledge work output are we about to see?"As Damian Player put it: "the people learning this now will be untouchable in 3 months." Whether that's aspirational or cautionary depends on your perspective.
Source Posts
Someone curated 925 failed VC-backed startups, broke down why they failed, and how to make it work with today’s tech - https://t.co/NFUhrhe7P2 Cool fr🙌 https://t.co/vOv2fUDnhY
This has been said a thousand times before, but allow me to add my own voice: the era of humans writing code is over. Disturbing for those of us who identify as SWEs, but no less true. That's not to say SWEs don't have work to do, but writing syntax directly is not it.
My top 3 tips for coding with agents: 1. Always start with Plan Mode. It's better to iterate in natural language and then execute once you know what the agent is going to do. This will save you time, effort, and tokens! 2. Start new chats frequently. Remember that your role is to point the Agent in the right direction to make the changes you need. If you change topics, the context window will get muddied. You will also be spending more tokens on longer chats. 3. Leverage AI to do your code review. If you know the failure case, ask a model. One prompt I often use is "scan the changes on my branch and confirm nothing is impacted outside of my feature flag". As a safety net for everything outside this issues-you-expect umbrella, use Bugbot.
This has been said a thousand times before, but allow me to add my own voice: the era of humans writing code is over. Disturbing for those of us who identify as SWEs, but no less true. That's not to say SWEs don't have work to do, but writing syntax directly is not it.
AI Agents 102
So, you've built an agent that kinda barely works in demos and now you want to deploy it for real users with real use cases. Demos and production have...
Remotion now has Agent Skills - make videos just with Claude Code! $ npx skills add remotion-dev/skills This animation was created just by prompting 👇 https://t.co/hadnkHlG6E
My top 3 tips for coding with agents: 1. Always start with Plan Mode. It's better to iterate in natural language and then execute once you know what the agent is going to do. This will save you time, effort, and tokens! 2. Start new chats frequently. Remember that your role is to point the Agent in the right direction to make the changes you need. If you change topics, the context window will get muddied. You will also be spending more tokens on longer chats. 3. Leverage AI to do your code review. If you know the failure case, ask a model. One prompt I often use is "scan the changes on my branch and confirm nothing is impacted outside of my feature flag". As a safety net for everything outside this issues-you-expect umbrella, use Bugbot.
This has been said a thousand times before, but allow me to add my own voice: the era of humans writing code is over. Disturbing for those of us who identify as SWEs, but no less true. That's not to say SWEs don't have work to do, but writing syntax directly is not it.
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Here's what we've learned from building and using coding agents. https://t.co/PuBtYuhyhd
Vibe Kanban: orchestrate multiple AI coding agents in parallel. Free and 100% open-source. Switch between Claude Code, Codex Gemini CLI, and track task status from a single dashboard. https://t.co/XfZLWpevqM