OpenClaw Early User Reports Telegram Issues, Agent Profile Hardcoding, and Session Reset Problems

A developer shared their initial experience with OpenClaw after getting it running locally via Docker. They conducted micro tests to understand features and token consumption, connecting Telegram as their first communication channel and linking the Wacli skill for WhatsApp using two phone numbers, plus setting up an initial heartbeat.
Key Observations from Testing
The user noted that many initial orientation problems aren't discussed by content creators who focus on simplicity. Their specific findings include:
- Telegram Blackout Response: Responses on Telegram randomly disappear and reappear, suggesting communication issues between Telegram and OpenClaw, possibly due to wake-up delays.
- Agent Profile Hardcoded: The agent profile was set to "messaging" and couldn't be changed through normal editing. The user discovered it's hardcoded in the source code and manually changed it to "full" for testing.
- Session Reset Issues: When resetting or starting a new session, the agent loses access to Wacli even though it remains active and authenticated. A workaround prompt is needed to restore access, indicating Wacli falls out of the agent's path after reset.
The user concluded that testing and breaking things reveals OpenClaw's nature as a solid foundation for building agents on top. They requested community input on similar issues and solutions, plus recommendations for initial setup and memory management, noting their setup appears to be missing something.
📖 Read the full source: r/openclaw
👀 See Also

Anthropic's Claude for Open Source program grants free Claude Max to qualifying maintainers
Anthropic offers six months of free Claude Max access to open source maintainers whose projects have 5,000+ GitHub stars or 1M+ monthly npm downloads with active commits in the last three months.

ThermoQA: Open Benchmark for Engineering Thermodynamics Tests LLMs on 293 Calculation Problems
ThermoQA is an open benchmark with 293 engineering thermodynamics problems across three tiers, testing LLMs on exact numerical calculations. Claude Opus 4.6 leads with 94.1% composite score, while DeepSeek-R1 shows highest run-to-run variance at ±2.5%.

Linux kernel developers propose removing legacy code due to LLM-generated bug reports
Linux kernel developers are proposing to remove several legacy subsystems including ISA/PCMCIA Ethernet drivers, amateur radio protocols, ATM, and ISDN to reduce the burden of handling security bug reports generated by large language models.

PrismML's Bonsai 1-bit Qwen models tested: 107 t/s generation on 8GB VRAM
Bonsai models from PrismML are 1-bit quantized versions of Qwen3 8B, 4B, and 1.7B that achieve 107 tokens/second generation and >1114 t/s prompt processing on an RTX 4060 with 8GB VRAM, with significantly reduced memory requirements.