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🤝 Top Collaborators
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🤓 Latest Submissions
Sentinel Swarm
Right now, AI coding tools only fix bugs a human already found. They wait for a ticket. Sentinel Swarm doesn't wait — it goes looking. We send four IBM Bob 2.0 subagents into a codebase with no bug report and no hints. Scout reads the code and figures out what each function is supposed to do. Saboteur then writes a real test targeting the edge case most likely to break it — empty input, a missing field, a boundary number. We actually run that test. If it fails, that's not a guess dressed up as an insight — it's proof, on screen, in real time. Medic then writes a fix and re-runs the exact same test to confirm it now passes. Scribe writes up what happened in plain English: what broke, why, how it was fixed, and how severe it was. That's the whole idea in one sentence: most tools suggest bugs, we prove them. Target users are developers and engineering teams shipping code faster than they can review it — exactly the gap current research (the Active-SWE benchmark) shows AI agents are weakest at: proactively finding problems nobody asked about. Sentinel Swarm turns that weakness into the entire product. A judge doesn't need to install anything or trust our word for it. They visit the live app, pick a scenario (or paste in their own small Python snippet — safely checked and sandboxed before anything runs), and click one button: "Release the Swarm." Four panels light up in sequence as the real chain runs — Scout mapping, Saboteur attacking, a test visibly failing, Medic patching, the same test turning green, and a case-file card assembling itself with a severity score and a "proven, not guessed" badge. The whole thing takes under two minutes and needs nothing from the judge but a click. What makes this different from existing AI code review tools isn't cleverness — it's a rule we never break: nothing is reported as a bug unless we've watched it fail with our own eyes. That single constraint is also our safeguard against hallucination — if the generated test doesn't actually fail, there's no finding, no report, no false claim. Efficiency-wise, this replaces a process that today requires a human to notice something's wrong, write it up, wait for someone to pick it up, and only then get a fix — often after the bug's already shipped. Sentinel Swarm collapses that entire cycle into one autonomous, self-verifying loop, running end to end in under two minutes with zero human bug report required. Built entirely on IBM Bob 2.0's Agent mode and subagent architecture — every "smart" decision in the pipeline is a real Bob call, not hardcoded logic pretending to be one.
27 Sep 2026
RadarAI — Competitive Intelligence Copilot
RadarAI is an AI-powered competitive intelligence platform built for B2B sales teams, account executives, product marketers, and founders. Competitors constantly change pricing, launch features, and reposition their products. Yet sales teams often rely on static battlecards that quickly become outdated, while product marketing teams spend hours manually monitoring competitor websites. This creates an information gap between what competitors are doing and what sales teams know. RadarAI closes that gap. Users add competitors and their domains to RadarAI. Bright Data provides live web intelligence from public competitor websites, allowing RadarAI to monitor relevant pages and identify meaningful changes. These changes are classified into competitive signals such as pricing shifts, product launches, and positioning changes. The raw information is then passed to an LLM through Featherless AI, where it is transformed into structured competitive intelligence: threat levels, strategic implications, competitor strengths and weaknesses, and recommended sales responses. RadarAI then turns this intelligence into AI-generated battlecards that sales teams can use immediately. Its Counter-Pitch Generator goes one step further: a salesperson can enter a real customer objection such as “They're 30% cheaper”, and RadarAI generates concise, context-aware talking points designed to help the salesperson respond. The core idea is simple: Don't just tell sales teams what changed. Tell them what it means — and what to say next. RadarAI is built with Native.builder and Claude Code, with Bright Data powering web intelligence, Featherless AI powering analysis and generation, and Supabase supporting persistent application data. A demo-safe fallback mode ensures the core experience remains usable even when external APIs are unavailable. Monitor → Understand → Act.
10 Aug 2026
