By the Exosolve Team

The Signal

Sharp takes on AI engineering, shipped weekly. No fluff, no hype — just what matters for teams building with AI in production.

Mar 26, 2026Industry3 min read

Claude 4.5 Changes Everything for Enterprise RAG

Anthropic just dropped Claude 4.5 with a 1M token context window and dramatically improved instruction following. For anyone building RAG systems in production, the calculus just shifted hard.

Mar 19, 2026Opinion

Why We Stopped Using LangChain (And What We Use Now)

After 14 months in production, we ripped LangChain out of three client projects. The abstractions that felt helpful in prototyping became a nightmare at scale. Here's what replaced it.

LangChainPythonArchitecture

4 min read

Mar 12, 2026Product

The Real Cost of Running AI in Production: Our Numbers

Everyone talks about AI costs in theory. We're sharing our actual production numbers — API spend, infrastructure, human oversight — across three enterprise deployments. The results might surprise you.

CostsProductionInfrastructure

4 min read

Feb 27, 2026Research

Groq's LPU vs NVIDIA GPUs: Benchmark Results That Surprised Us

We ran identical workloads on Groq's LPU Cloud and NVIDIA A100s via AWS. The latency numbers are stunning, but the story is more nuanced than the hype suggests.

GroqNVIDIABenchmarks

3 min read

Feb 20, 2026Industry

MCP Protocol: The Missing Piece for Agentic AI

Anthropic's Model Context Protocol is quietly becoming the USB-C of AI tool integration. After implementing it across four client projects, we think it's the most important AI infrastructure development since vector databases.

MCPAnthropicAgents

3 min read

Feb 13, 2026Product

We Built an AI That Reviews Contracts 160x Faster. Here's What Went Wrong First.

LEXIS AI now processes contract reviews 160x faster than a senior associate. But our first three versions were unusable disasters. Here's the honest story of what failed and why.

LEXISLegal AIContract Review

4 min read

Jan 29, 2026Opinion

The RAG vs Fine-Tuning Debate Is Over. Here's Why.

The AI community loves binary debates. RAG or fine-tuning? The answer has been clear for months to anyone actually shipping production systems: it depends, and increasingly, it's both.

RAGFine-TuningArchitecture

3 min read

Jan 15, 2026Product

How We Cut Our AI Infrastructure Costs by 85%

Our first production AI deployment cost $23K/month. After six months of optimization, we got it to $3.4K/month with better performance. Here are the seven techniques that actually moved the needle.

Cost OptimizationInfrastructureCaching

4 min read

Jan 8, 2026Industry

Anthropic's Computer Use Changed How We Think About AI Agents

When Anthropic released Computer Use, most people saw a party trick. We saw the future of enterprise automation — and immediately started rebuilding our agent architecture around it.

Computer UseAnthropicAgents

3 min read

Dec 18, 2025Opinion

Vector Databases Are Overengineered for 90% of Use Cases

Pinecone, Weaviate, Qdrant, Milvus, Chroma — the vector database market is exploding. But most teams using them would get identical results with pgvector and save themselves a world of operational pain.

Vector DatabasepgvectorPostgreSQL

3 min read