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Heavybit, Radar, and Gather.dev Push Engineering Past Autocomplete: The New Agentic SDLC

Heavybit, Radar, and Gather.dev Push Engineering Past Autocomplete: The New Agentic SDLC

Engineering teams are entering a new phase of the AI cycle, and the implications are starting to register across the startup ecosystem. For years the conversation centered on speed. Faster commits. Faster code suggestions. Faster iterations. That was the autocomplete era. What is emerging now is something different. Engineers are beginning to supervise systems that can reason through real engineering tasks. Context becomes the leverage point and the codebase becomes the proving ground. The practical question facing technical leaders is no longer whether AI can assist development. The real question is how engineering organizations evolve when intelligent systems begin participating across the software development lifecycle.

That tension is exactly why a specific room in New York is about to matter. On March 31 from 6 to 9 PM, inside Radar’s office at 111 5th Ave on the 12th floor in Flatiron, a curated group of engineering leaders will gather for an event called The New Agentic SDLC. The room is deliberately small. Registration requires approval. The audience is Staff+ engineers, engineering directors, VPs, CTOs, and dev tool founders who influence how modern engineering organizations actually operate.

Heavybit, Radar, and Gather.dev are bringing the room together. In the developer infrastructure world, Heavybit has spent years investing in and cultivating the companies engineers rely on once systems become real businesses. Radar approaches location infrastructure the way a platform company approaches gravity. Their Flatiron office becomes the physical coordinate for a conversation already spreading through the startup ecosystem. Gather.dev adds another layer of signal. The community, curated by Peter Bell, is built on a simple premise: senior engineering leaders do not need more noise. They need sharper conversations with peers who understand the scale of the problems.

The format reflects that philosophy. Short demos. Presentations. Interviews. An engineering leadership panel. The kind of discussion that usually happens after conference stages go dark and operators start comparing what is actually working inside their codebases. Food and drinks will be there, but the real draw is the exchange of operational insight among people responsible for engineering velocity, tooling decisions, and architectural direction.

The backdrop is bigger than one event. The jump from augmented coding to agentic engineering arrived faster than most teams expected. When models like Opus 4.5 and Codex 5.2 appeared, autocomplete stopped being the headline. Engineers started having what many describe as the “claude code moment,” that instant when the model behaves less like a suggestion engine and more like a junior engineer who simply needs context and guardrails.

That is where the real challenge begins. Demos are easy. Legacy systems are not. Most engineering organizations operate inside brownfield codebases layered with years of architectural decisions. Scaling agentic workflows across that reality requires trust models, governance, and practices that can propagate across large teams. Those are the questions quietly moving through the startup ecosystem, especially among companies building developer tools and AI infrastructure.

Rooms like this appear when a technical shift begins moving from curiosity to operating model. The New Agentic SDLC is less about predictions and more about practitioners comparing notes at the edge of a transition. What happens in rooms like this rarely stays contained. Ideas migrate through the startup ecosystem, shaping how teams build, how platforms evolve, and how the next generation of software engineering gets defined.