Alternatives
Products that do what Signal Sense: Decode does
Decode the hidden patterns behind any situation
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2015 · jackschaedler.github.io
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Hey there! Signals is a survey system that collects feedback from staff (mostly) but also clients and stakeholders in a business. It does this via SMS on a weekly schedule (the cadence can be changed but it works best when done weekly). My co-founder and I started working on this nearly a year ago, having run similar small builds for over four years. This time we’ve tried to do it properly. The execution is relatively simple - similar to an eNPS (Net Promoter Score - a common way of measuring how consumers like your product or service), but we wanted a way to anonymously pass candid feedback…
2023 · runsignals.com
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2025 · alexandrefrancois.org
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I put together a repo called Spoon-Bending, it is not a jailbreak or hack, it is a structured logical framework for studying how GPT-5 responds under different framings compared to earlier versions. The framework maps responses into zones of refusal, partial analysis, or free exploration, making alignment behavior more reproducible and easier to study systematically. The idea is simple: by treating prompts and outputs as part of a logical schema, you can start to see objective patterns in how alignment shifts across versions. The README explains the schema and provides concrete tactics for…
2025 · github.com
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Your AI has your code's text, never its map. Fix that.
Jun 2026 · luuuc.github.io
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A 100% local extension to analyze web page atmosphere
24d ago · layerofsignal.github.io
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AI that decodes mixed signals and ambiguous texts
Jun 2026 · getexray.app
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The most common failures for production agents are behavioral: looping, reasoning leakage, user frustration, and more. Using a frontier model like GPT or Sonnet to judge every turn is too expensive and slow to run at scale. To solve this, we built Reflexes: semantic signals from agent traces, served fast and cheap over API. Built on custom kernels and a custom inference engine forked from vLLM. Under the hood, it is a small LLM architected around multi-head inference. Small models need to be trained for specific tasks, but running 50 separate small models on the same input for 50 tasks makes…
Jun 2026
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