My fav part of autocoding is that it allows me to attempt much more ambitious projects than I otherwise would have bothered with, which is incredible for building learning/understanding if done right.

What happens when I use autocoding is *very* strange, is something that didn't exist in myself, in the past. I write big chunks of text to the LLM and every word I type I "feel" how it is going to condition the work of the agent in one way or the other. Every word reduces the error.

if you hire random dprk it workers especially with autocoding these days you deserve to get rekt

One of the most powerful automatic coding (autocoding) trick that almost nobody uses: "Create this new project as specified in SPEC.md using as guide for coding style, design sensibility, comments, ..., the code at /foo/bar/". Style transfer is very powerful.

everyone could reasonably expect with AI autocoding that a smart contract developer would proceed to build everything in defi from zero / first principles. That is zFi.

Autocoding: like vibecoding, except using the better tools we have that actually work now Autocoder: any program that you can use to autocode

Brex shifts accounting from batch closes to continuous AI-driven ledger sync. Claims 10,000 hours of manual work eliminated. Real agentic deployment—or autocoding errors waiting to compound? Brex Brings AI-Native Accounting Automation to ERPs buff.ly/PurQAqQ

People are excited about Ralph Wiggum, but @blocks and @jack quietly released what I'm dubbing Principal Skinner, an adversarial feedback loop to better ensure complex task success. "Adversarial Cooperation In Code Synthesis" >This paper introduces dialectical autocoding: a novel approach to AI-assisted software development that transcends the limitations of current vibe coding tools through a structured coach-player feedback loop. By implementing a bounded, adversarial process between two cooperating agents, we demonstrate how intelligent AI programs can make substantially more progress on complex coding tasks, resulting in better tested, more robust implementations, while working around fundamental attention and human-in-the-loop limitations.

Not gonna be active on Discord tonight. I'm meeting an agentic MCP-enabled toolcalling orchestration stack with a fully wired planner/router/executor loop, tight context budgeting, progressive disclosure, and a permissions-gated action surface (a real one) in half an hour (wouldn't expect a lot of you to understand anyway) so please don't DM me asking me where I am (im with Claude Code Opus 4.5 holiday doubled usage limits building recursive self-autocoding subagents that emit their own eval probes and rollback triggers, all inside a scoped-permissions, human-approval-gated, MCP-connected capability mesh, with LSP IDE signal hook workflows doing tool selection, argument marshaling, post-call verification, and bounded capability escalation, ok) you'll most likely get aired because I'll be pushing MCP-scoped routing into GPT-5.2-Codex for long-horizon diffs, GLM 4.7 as the long-running executor worker, Playwriter as the browser leg for grounded repro/retrieval, and a 24 hour checkpointed run (because ill be meeting an agentic MCP-enabled toolcalling orchestration cluster with a fully wired planner/router/executor loop, tight context budgeting, progressive disclosure, and a permissions-gated action surface, not that you really are going to understand)

This is not a research, this is not new. "dialectical autocoding" is just agent ping-pong. You make it sound like you've invented something

Every investor in Block should read this research to better understand how we’re constantly evolving to automate our company. Next step on the journey: dialectical autocoding

Block just dropped “Adversarial Cooperation in Code Synthesis” – a fresh take on AI-assisted dev via dialectical autocoding. Core: Coach-player agent dyad in g3 framework. Player implements/tests code; coach validates vs. requirements, delivers precise feedback. Fresh contexts per turn dodge pollution; bounded loops (e.g., 10 turns) drive autonomous progress. Beats “vibe coding” limits: superior focus, refinement, complexity handling. Case studies (Calculator API, Git TUI, iOS app) score g3 5/5 completeness vs. Goose/OpenHands/Cursor – full test coverage, no crashes, multi-hour autonomy. TL;DR: Structured adversarial reasoning unlocks robust, human-free coding sessions. Game-changer for agentic benchmarks. Paper: block.xyz/documents/adversar…

$XYZ dialectical autocoding: a novel approach to AI-assisted software development that transcends the limitations of current vibe coding tools through a structured coach-player feedback loop.

dialectical autocoding –– a novel approach to AI-assisted software development that transcends the limitations of current vibe coding tools through a structured coach-player feedback loop.

dialectical autocoding: block.xyz/documents/adversar… new research by block AI (block.xyz/ai)

Even for AI standards. Gemini is incredibly subpar compared to ChatGPT, Copilot or grok. It's autocoding is weaker, its response times slower and the answers are less specific. Also, it's behind a paywall unlike the others So, it doesn't surprise me their AI has gone full retard

We’re cooking 🧑‍🍳 something new at @yepcode_io that will change how developers build integrations. Stay tuned 👀 #AIDrivenDevelopment #AutoCoding #IntelligentAutomation #DX #AICodeExecution #SandboxSecurity #EnterpriseReady #WhenYouGraduateFromNoCodeTools

Low-Code & No-Code vs Autocoding💥 Low-code and no-code promised speed, but without AI they couldn’t scale or solve the core bottleneck. Copilot helps programmers, but it doesn’t replace coding itself. 💡Autopilot does. AutoCoder generates complete apps end-to-end, from idea to deployable code, without a human typing each line. This is the future AutoCoder is building — Autocoding, not just assistance. 🤖 #AutoCoder #AI #Automation #NoCode #FutureOfWork

First Light has taken a large open market position in ai16z. Crypto has always been about leveraging permissionless systems to solve hard problems. And agents are the new nexus. Machine-to-machine commerce, identity & reputation, private coordination, and trust without trust. The solvers of said problems will print. After listening to Shaw speak and gronking around in the discord it is obvious that elizaOS presents a clear case of a lotus yet to bloom. All the hard work is happening in the mud, yet price and investor sentiment centres on only one fact — that the flower has yet to bloom. // Most investors don’t even know what elizaOS is. And the token is steeped in reputational debt and owned by users with a dislocated temporal sense. That’s precisely why it is interesting to us at First Light. // First Light advocates for a content pivot with the following recommendations: Strapline: The Agent Singularity Starts Here. Context: The singularity is a threshold where agents stop being task-specific tools and start operating with autonomy in unstructured environments. Today’s agents are boxed in LLMs with wheels, and elizaOS is the first framework meaningfully looking to autonomy. Everything is a plugin // every capability is bolted onto the agent. Extensibility is the moat, and elizaOS has the compounding edge. Every day the registry grows, agents get sharper, and the singularity draws nearer. In a literal sense, elizaOS is compiling the future in real time. // The Problem Today’s agents are gated and fragile. The Bet Agent dominance stems from networked capability // elizaOS unifies actions and environments under a single plugin layer and will eat the agent stack Why take a position now? LLMs are being commoditized: GPT-5 was not a step up but a linear improvement. Value will migrate to orchestration and action. It will flow from infra to apps, and from general intelligence to specific niches. // Recommended Core Narrative Angles: 1. The Agent Singularity elizaOS is at the forefront of on-chain AGI // it is the first enterprise focused on building the only thing worth building // a system that builds itself 2. The Trillion Dollar Composable Agent Economy agent-to-agent commerce on-chain is the next trillion-dollar market // elizaOS ships abilities that every agent can reuse flywheel: more abilities, more agents, more usage of abilities, better feedback of abilities, more upgrades 3. Own the System That Scales Itself elizaOS has been constructed as a force multiplier with autocoding for plugins that scale capabilities exponentially // this is thanks to its specialization as being as AI code-friendly as possible 4. The Plugin Operating System everything is a plugin // literally everything The last decade centered on digitizing industries // the next decade will focus on autonomizing them. // Agents = programmable labor elizaOS = the factory of factories Welcome to the agent epoch.

Perils of autocoding You don't get interested in fixing bugs.. and depend on the AI tool Becomes so lazy although you have skillset to debug Experiencing it first hand