Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
Crews give agents autonomy; Flows give you precise control. The 2026 production answer is to nest one inside the other — Flows as the spine, Crews as the muscle. Real CallSphere examples and a decision matrix.
Voice agents emit ASR latency, TTS latency, barge-in counts, and turn-level token use. TimescaleDB's hypertables + continuous aggregates handle billions of rows while keeping dashboards under 200 ms.
VS Code Copilot, Cursor, and Claude Code render syntax-highlighted code blocks with copy and apply buttons. Here is how 2026 chat agents emit, render, and execute code inline.
When the caller interrupts, you have ~200ms to detect and ~300ms to stop. We engineer full-duplex barge-in with VAD, echo cancellation, buffer flushing, and context tagging — production-grade for 2026.
Off-the-shelf WAFs don't parse SIP and bypass WebSocket payloads. Here is the 2026 rule set that catches WebRTC-specific abuse: SDP injection, WS protocol smuggling, and TURN allocation floods.
DSPy compiles natural-language signatures into optimized prompts and demonstrations. MIPROv2 (Bayesian optimization over instructions + few-shot exemplars) consistently delivers 10–40% quality lift over hand-written prompts on structured tasks.
Convex's Agent component gives you persistent threads, live-updating message history, and reactive tool-call progress — all on top of websocket queries.
SMB tier-1 IT tickets — passwords, VPN, software access — represent 50–80% of volume. Here is the 2026 chat playbook that hits 60–80% autonomous resolution without breaking on edge cases.
Anthropic's prompt cache cuts cached input tokens to 0.1x base price — a 90% discount. We map the 5-min vs 1-hour TTL math, the cache_control placement rules, and the layout that drops CallSphere's Claude bill from ~$4,200/mo to ~$420/mo on a 12k system prompt.
