“in Dharmesh Shah advocated an “open brain” approach that makes organizational information machine- and human-readable, citing Jeff Bezos’s vision for interactions through well-defined APIs.”

#7 in Dharmesh Shah advocated an “open brain” approach that makes organizational information machine- and human-readable, citing Jeff Bezos’s vision for interactions through well-defined APIs. Shah also announced that he is working on an unnamed HubSpot Next project, now in private beta, to help entrepreneurs establish this groundwork.

“𝕏 Dharmesh Shah introduced a new conversational interface for building agents alongside the classic UI, arguing that blending fresh tools with familiar workflows—drawn from his 30+ years in human-centric software design—eases user adoption.”

𝕏 Dharmesh Shah introduced a new conversational interface for building agents alongside the classic UI, arguing that blending fresh tools with familiar workflows—drawn from his 30+ years in human-centric software design—eases user adoption.

“Dharmesh Shah celebrates HubSpot’s public beta launch of Agent Hub and Agent Builder, a toolkit that lets you build custom chat-style AI agents or agentic workflows by mixing your data, tools, and prompts.”

#9 𝕏 Dharmesh Shah celebrates HubSpot’s public beta launch of Agent Hub and Agent Builder, a toolkit that lets you build custom chat-style AI agents or agentic workflows by mixing your data, tools, and prompts. #10 𝕏 Philipp Schmid : LangChain now lets you trace GoogleDeepMind Gemini Live speech-to-speech loops in real time—featuring speaker callback hooks, a color-coded live timeline (user in blue, Gemini in orange, tools in custom colors), and separate audio vs.

“#22 in Dharmesh Shah urges teams to avoid using LLMs to infer data that can be directly retrieved with structured queries like SQL. He highlights that SQL is far more cost-effective, faster, and predictable.”

#22 in Dharmesh Shah urges teams to avoid using LLMs to infer data that can be directly retrieved with structured queries like SQL. He highlights that SQL is far more cost-effective, faster, and predictable.

“in Dharmesh Shah launched HubSpot’s private-beta Agent CLI, a next-gen command-line tool built for agentic workflows.”

#21 𝕏 in Dharmesh Shah launched HubSpot’s private-beta Agent CLI, a next-gen command-line tool built for agentic workflows. He argues the future of software lies in humans (for context, judgment, creativity) and AI agents (for speed, scale, patience) collaborating.

“#5 𝕏 Dharmesh Shah argues that while AI models now excel at reasoning and large-context understanding, it’s the harness—platforms like ChatGPT or Claude Cowork that supply tools, memory, skills, and context—that truly turns a powerful model into a usable product.”

#5 𝕏 Dharmesh Shah argues that while AI models now excel at reasoning and large-context understanding, it’s the harness—platforms like ChatGPT or Claude Cowork that supply tools, memory, skills, and context—that truly turns a powerful model into a usable product. #18 in Dharmesh Shah emphasizes that AI platforms like ChatGPT and Claude Cowork—providing tools, memory, skills and context—matter far more than the underlying model alone.

“in Dharmesh Shah announces Andrej Karpathy has joined Anthropic to use Claude to accelerate AI research, underscoring the huge leverage of AI-powered research loops.”

#10 in Dharmesh Shah announces Andrej Karpathy has joined Anthropic to use Claude to accelerate AI research, underscoring the huge leverage of AI-powered research loops.

“Dharmesh Shah says HubSpot is launching an agentic experience (AX) so AI agents can natively configure the platform, create dashboards, and fully manage the CRM instead of relying on a human UX.”

#19 𝕏 Dharmesh Shah says HubSpot is launching an agentic experience (AX) so AI agents can natively configure the platform, create dashboards, and fully manage the CRM instead of relying on a human UX.

“#5 𝕏 Dharmesh Shah argues that legacy APIs assumed human developers who’d read docs and iterate, but as agents become the primary users, APIs, MCPs, and CLIs must be redesigned to be more discoverable, legible, and forgiving.”

#5 𝕏 Dharmesh Shah argues that legacy APIs assumed human developers who’d read docs and iterate, but as agents become the primary users, APIs, MCPs, and CLIs must be redesigned to be more discoverable, legible, and forgiving. #8 𝕏 Dharmesh Shah applauds HubSpot for topping @jasonlk’s “agent readiness” list, underscoring that software must deliver not only stellar human UX but also robust agentic experiences (AX).

“#11 𝕏 Dharmesh Shah argues that differentiating durable value with a frontier model + harness is harder than leveraging deep, years-long accumulation of data and context.”

#11 𝕏 Dharmesh Shah argues that differentiating durable value with a frontier model + harness is harder than leveraging deep, years-long accumulation of data and context. He also doubts we’re heading toward an AI “-mageddon.”