by iqentity | Jun 17, 2024 | Development, Tessera
Semantic search is Tessera’s primary retrieval mechanism for conceptual matching, and the embedding strategy required careful thought. Off-the-shelf embeddings are trained on generic text. Tessera’s corpus is anything but generic. The Domain Collision...
by iqentity | Jun 13, 2024 | Development, Tessera
Theory is comfortable. Production is not. I have been running Tessera in parallel with my normal workflow for six weeks, using it during actual client situations and comparing its output to what I would have done without it. The results are encouraging, humbling, and...
by iqentity | Jun 4, 2024 | Development, Tessera
The prompt engineering for Tessera is unlike any other prompt work I have done. I am not designing prompts for a general-purpose assistant. I am designing prompts for a system that needs to think like me, respond in patterns I find useful, and maintain a level of...
by iqentity | May 23, 2024 | Development, Tessera
Tessera will get things wrong. Not occasionally. Regularly. The local language model hallucinates. The graph traversal sometimes follows a misleading path. The enrichment pipeline misclassifies decisions. The salience model under-weights artifacts that turn out to be...
by iqentity | May 19, 2024 | Development, Tessera
Most AI systems are trained on outputs. What was the answer? What was the decision? Tessera is also trained on corrections. Where did I change my mind, and why? Why Corrections Matter More Than Conclusions A system that only learns from final decisions becomes...
by iqentity | May 16, 2024 | Development, Tessera
The remediation and professional support capabilities are what justify building Tessera. The life orchestration capabilities are what make it indispensable. There is a difference between a tool you use when something breaks and a system you rely on to keep things from...
