I’ve gotten many requests to change our weekly webinar time! So this week we will be doing this new time to see how it goes. I also want to encourage you to attend! We have people sharing insights on what’s working and how to make real progress. We do our best to make it one of the most valuable hours of your week. See you tomorrow!

GPT-5.6 Sol just entered limited preview, and it looks like a major step for agentic coding + security work. Quick context: OpenAI announced GPT-5.6 Sol, Terra, and Luna today. Sol is the new flagship model, but it is not broadly available yet. During preview, OpenAI says GPT-5.6 is only available through API + Codex to a select group of trusted partners/organizations, with broader ChatGPT, Codex, and API access coming soon. So if you are on ChatGPT Pro and wondering why you do not have it yet, that seems normal. Pro does not appear to unlock this preview by itself. The part that caught my eye: OpenAI says GPT-5.6 Sol is competitive with Mythos Preview on ExploitBench while using roughly one third of the output tokens. That is a big deal for long-running agent work, where token efficiency matters almost as much as raw benchmark score. OpenAI's system-card chart for ExploitBench shows Sol pushing the performance/token frontier ahead of GPT-5.5 and GPT-5.4. For ProductiveBot/OpenClaw users: OpenClaw should be able to route GPT-5.6 once OpenAI exposes it to the connected Codex account. Right now, our available Codex model list still shows GPT-5.5, not GPT-5.6, so this is watch closely territory rather than switch today. Hermes users should watch this too. Hermes benefits from the same kind of model improvements: better long-running reasoning, better coding reliability, and lower token waste during multi-step work. Once GPT-5.6 is actually exposed to connected accounts, the practical question will be how it performs inside real Hermes/OpenClaw workflows, not just benchmarks. Sources: https://openai.com/index/previewing-gpt-5-6-sol/ https://deploymentsafety.openai.com/gpt-5-6-preview/gpt-5-6-preview.pdf

OpenClaw 2026.1.15 is out. This is not an emergency update for most ProductiveBot customers, but there are a few things worth knowing before you upgrade or troubleshoot. What matters: - iPhone and iPad users: the native iOS app now requires iOS 18.0 or newer. If your device is older or not updated, check before updating the app. - Microsoft Teams users: Teams is now handled as a plugin. If your assistant is connected to Teams, do not update blindly. Make sure @clawdbot/msteams is installed and configured, or ask us to help. - Login and model setup should get smoother: plugin-driven OAuth/API key flows are now supported through clawdbot models auth login. - Browser automation should be more reliable, especially for remote Chrome or Browserless setups. - Security is tighter: audits now warn about weaker model tiers, and app node auth tokens are stored encrypted. Our recommendation: If your ProductiveBot setup is working well and you are not affected by iOS or Teams, you can wait. If you do update, run the normal validation after the upgrade and test your main workflow before treating it as complete. If you use Teams, iOS, browser automation, or custom model/provider auth, drop a note here before updating and we can help you avoid the common gotchas. Source: https://github.com/openclaw/openclaw/releases/tag/v2026.1.15

OpenClaw 2026.6.10 is out, and this release is mainly about stability and day-to-day reliability. Why it matters: - Short, simple requests should feel faster - Model routing should be more reliable - Session state and trusted policies are safer - Provider setup/onboarding should be smoother The most important part for ProductiveBot users is the routing reliability work. When model routing is flaky, assistants can feel inconsistent or randomly fail during normal workflows. This update is aimed directly at that kind of reliability problem. Community reaction so far is mostly positive. People are specifically calling out better stability, faster short interactions, and routing improvements as meaningful. That said, there are still a few caution signs around config issues and speed, especially from users comparing OpenClaw with Hermes. Our recommendation: If you are comfortable updating and have time to troubleshoot if needed, this looks like a good version to try. If your current setup is stable and you rely on it heavily every day, it is reasonable to wait a few days before updating. If you are a ProductiveBot customer and you are unsure, ask us first. We can help you decide based on your setup.

The short version: agentic AI is moving from "cool demo" to operational infrastructure. The loudest signals are memory, local-first runtime, tool orchestration, governance, and reusable workflows. What moved recently: - Claude Cowork / computer use: strongest chatter is around practical workflows, Microsoft 365 integration, and easier handoffs. - OpenClaw updates: light but positive mentions around v6.8, runtime infrastructure, and agent improvements. - Model shifts: voice upgrades, coding models, and local optimization are all getting attention. What builders are sharing: - LangGraph, CrewAI, and OpenAI Agents Python are still common picks. - Vercel Eve and Omnigent are getting attention for durable execution, sandboxes, and evals. - Local memory projects are a big theme: agents need persistent context without burning tokens. - MCP servers, browser tools, context compression, and workflow automation are becoming table stakes. - Security is getting more serious: per-agent identity, MCP gateways, audit logs, and policies are showing up more often. Why this matters for ProductiveBot: 1. Memory and compression are becoming core infrastructure. People want agents that remember the work. 2. Tool adapters are the product surface. The winning agents will be defined by how reliably they use browsers, files, APIs, calendars, code, email, Slack, and workflows. 3. Local-first is turning into a trust signal. People are paying closer attention to where the agent runs and who controls the data. 4. Governance is becoming part of the buyer checklist. Anyone giving an AI real tools eventually needs guardrails. My read: the market is shifting from "which model is smartest?" to "which system can do useful work safely, repeatedly, and with memory?" That is good news for ProductiveBot. The opportunity is making the operational layer of personal agents reliable enough for everyday business owners.