Know What to Build Before You Code.
Stop wasting weeks building software nobody buys. Signal gives developers and AI coding agents 100% sourced demand proof, commercial datasets, and 48-hour experiment gates—before writing a single line.
Sub-5ms Embedding Retrieval on Edge Runtimes without Python
Developers building desktop or WASM apps cannot ship 80MB ONNX runtimes. Need raw Int8 SIMD dot-products.
10k benchmark query-passage pairs verified for commercial use.
Mean latency < 18ms AND Recall@5 >= 82% vs brute force.
What is worth building?
Ranked, sourced technical bottlenecks mined from 500,000+ real developer and founder threads—never generic LLM ideas.
Will anyone pay for it?
Extracted dollar prices, admitted MRR figures, and post-mortems of competitors who failed before you write code.
How do I test it in 48 hours?
Every query generates an explicit numeric pass/fail threshold with named commercial datasets to prove feasibility fast.
The 3 Sunk-Cost Traps That Kill 94% of Software Projects
Why talented builders waste hundreds of hours coding solutions nobody asked for, or get misled by generic AI chatbots.
The Engineer's Blind Build
Engineers can build almost anything, but lack sourced proof of what is worth building. Generic AI outputs trivial todo apps and toy wrappers rather than commercial benchmarks and production failure modes.
The Founder's Manual Grind
Founders spend 4 weeks combing Reddit, Indie Hackers, and X by hand to gauge demand. They cannot objectively tell whether complaints indicate genuine willingness-to-pay or just idle vent posts.
The Generic LLM Hallucination
Standard LLMs are trained to be agreeable. They tell every builder their idea is brilliant, inventing non-existent datasets and proposing "launch an MVP this weekend" without verifying licenses, latency, or customer spending.
Two Modes to Eliminate Pre-Build Risk
Whether you are an engineer seeking an architecture spike or a founder validating market demand, Signal grounds you in reality.
Engineer Mode
Input: Loose technical interest (e.g., local vector search).
Output: Sourced problem severity, commercially licensed datasets, problem-type architecture, and an explicit 48-hour pass/fail experiment gate.
Founder Mode
Path A (Discovery): Mining unaddressed complaints ranked by recency and frequency.
Path B (Validation): Testing an idea against real stated prices and graveyard autopsies.
Signal vs. Naive Claude Baseline
Report target: >70% blind comparison win rate among AI/ML engineers before billing. Test the exact same query below.
Signal Pre-Build Engine
8.6/10: Sub-5ms retrieval without heavy 80MB ONNX runtime binaries (source: github.com/trending/ai/discussions/4192)
MS MARCO (CC-BY-4.0, 10k pairs) + BEIR Suite (Apache-2.0, 5k annotated passages) with direct repository URLs.
Explicit Numeric Gate: "Pass if p95 latency < 18ms across 200 random queries AND Recall@5 >= 82% against exact brute force."
Extracted Stated Price: $29 one-time dev license vs $70/mo ongoing Pinecone cloud spend cited by 14 desktop devs.
EmbedFast (shut down 2024): Failed due to Python C-extension compatibility issues on Windows ARM.
Naive Claude / Generic LLM
Building a vector database is a great idea! You can store embeddings in SQLite and calculate cosine distance in Python or JavaScript.
You can find many datasets on Kaggle or HuggingFace like Wikipedia or general text corpus.
"Build a prototype this weekend, test it with a few friends, and see if they find it useful."
"Consider charging a subscription like $19/month or offering a free open-source tier with paid cloud hosting."
None mentioned. ("Make sure to market your product effectively to avoid failure.")
Shared Retrieval Core & MCP Agent Attachment
Designed agent-first so developer agents (Claude Desktop, Cursor, Windsurf) query Signal directly via MCP.
Near-Zero Marginal Cost
Live retrieval, deduplication, freshness checks, and an embedding-based ranking path with zero LLM synthesis overhead. Fast, deterministic, and cheap.
Every Fact Has a URL & Timestamp
Every pain point, stated price, and dataset carries a real source_url and retrieved_at timestamp. Zero hallucinations.
Reasoning Tailored to You
Attach your personal builder profile. Signal automatically calculates whether recommended architectures and datasets fit your weekly timebox and cloud budget.
Metered Credits. Zero Hidden Lock-In.
Non-expiring credit allotments referencing MCP documentation-search baselines ($0.009/search).
- ✓ Raw indexing & semantic ranking
- ✓ 5 Engineer Mode complete briefs
- ✓ Full MCP / API access for Cursor
- ✓ Local dossier vault storage
- ✓ Everything in Free Tier
- ✓ Full Founder Mode demand scores
- ✓ Deep me.md personalized reasoning
- ✓ Automatic 2-week delta signals
- ✓ Bulk live feed licensing
- ✓ Per-agent key quotas & rate limits
- ✓ Redis query-level semantic cache
- ✓ Dedicated telemetry stream
Know your odds before writing line one.
Ground your next product in verified pain points, stated prices, named commercial datasets, and explicit 48-hour experiment thresholds.