Self Proclaimed #BotKiller | FOUNDER || #BigData Cruncher / #AdTech, “Data Royalties™”, LLM white paper connoisseur, and on a mission to Keep Data Human.
The LangChain post serves as a catalog of the failure modes encountered by modern deep agents, but it does not provide the correct solutions to address these issues.
#HarnessEngineering is fundamentally about coupling. LangChain demonstrates this #coupling through prompt strings and #Python#middleware, which can be likened to the 2026 equivalent of punch cards: a superficial grammar layered over a substrate that lacks essential semantic primitives.
It raises the question: when will the industry focus on addressing the root of the problem rather than just another petal of the 🌼?
For full LangChain post, visit the link: langchain.com/blog/improving….
Q: How do you protect the #AIBubble ?
A: You use bubble wrap, of course.
Insulate BIG 🫧 with smaller bubbles—i.e., $1B here, another $B there—and the mothership AI-bubble wrapped flywheel keeps churning.
Damn, I love🥰 bubble wrap! 🫧 🪽
.@shellypalmer fell down a meme “rabbit hole” courtesy of the “AI Slop” term and the parallel scene in Hannibal where Hopkins feeds the brain back to the human. Wanted to share a few AI Slop-generated memes.
shellypalmer.com/2025/07/bun…
FORCE CHATGPT to STOP HALLUCINATING and be RELEVANT
PROMPT
03 model “generate a Vector Mapping Logic Layer Rule Base for my uploaded knowledge relating to my company CustomGPT.”
3. Rule Base = Hard-codes behavioral boundaries—like “always format in Markdown,” “never speculate,” or “cite source when confidence < 90%.”
OUTCOME
You have a deterministic Custom GPT that follows rules, not a chatbot.
Make sure to Export all elements in correct format:
- OpenAI plugin or API use = JSON
- Embedding in GPT’s system instructions or files = TXT
- Documentation or Git-based change tracking = Markdown
The next evolution of #AI is shift from reactive to proactive.
Today’s AI is black & white—linear and reactive. Tomorrow’s AI will see in color, predicting trends before they emerge.
With real-time API data and local compute, #EnterpriseAI
Let me use 50% synthetic data to train an LLM for brain brain surgeons. It is only wrong only half the time…
But don’t worry I used digital twins so no real ppl were harmed during training.
OpenAI's Whisper fabricating medical records is a perfect example of why we need verification networks.
Decentralized consensus beats single-model hallucination risks in such high-stakes scenarios.
#AI is evolving: it’s not about bigger #LLM models but smarter, enterprise-tuned solutions. Intel & AMD positioned to lead, turning chips into business innovation engines. #EnterpriseAI 🌐💥
By integrating diverse API streams into internal datasets with local compute, your enterprise AI becomes a constantly adaptive engine for real-world impact.
#RealTimeData#EnterpriseAI