Poe × WorkDaddy: LLM Provider Integration (2026)

Use Poe as the engine behind your WorkDaddy agent team: 137 models available, context windows up to 2M tokens, connected in minutes with your own key.

Poe is one of 178 LLM providers supported by WorkDaddy’s model layer in 2026, in the Aggregators & Gateways group. The catalog currently lists 137 models from Poe: 71 with explicit reasoning, 94 with vision input, and 134 with tool calling — the capability that matters most for agent work. The largest context window reaches 2M tokens.

At a glance

Models available 137
Reasoning models 71
Vision models 94
Tool-calling models 134
Largest context window 2M tokens
API endpoint https://api.poe.com/v1
API key variable POE_API_KEY
SDK adapter @ai-sdk/openai-compatible
Provider docs creator.poe.com ↗

Why run WorkDaddy agents on Poe in 2026

Tool calling, context size, and cost decide how well a provider drives an agent team. Poe brings 134 tool-calling models to WorkDaddy — enough to power the full loop of storefront edits, analytics queries, and content production — with 2M tokens of context at the top end for whole-codebase and long-report work. Because WorkDaddy is model-agnostic, you can route heavy reasoning to Poe’s strongest model and bulk work to its cheapest, inside one team.

Best Poe models for e-commerce agents (2026)

The current flagships from Poe in the WorkDaddy catalog, newest first:

  • Claude-Opus-4.8 — Top Claude Opus tier for the hardest reasoning, coding, and long-horizon agents (1M context)

  • Gemini-3.5-Flash — Fast Gemini model balancing multimodal reasoning, tool use, and cost (1M context)

  • DeepSeek-V4-Flash-EL — Fast DeepSeek model for efficient chat, coding help, and agent loops (1M context)

  • DeepSeek-V4-Pro-EL — Flagship DeepSeek model for coding, reasoning, and agentic work (1M context)

  • GPT-Image-2 — Image model for prompt-driven generation, editing, and visual design workflows (0 context)

  • Kimi-K2.6 — Kimi multimodal agent model for visual understanding, coding, and planning (262K context)

How to connect Poe to WorkDaddy

WorkDaddy talks to Poe at api.poe.com via the @ai-sdk/openai-compatible adapter. Add your credential (typically POE_API_KEY) in Settings → Models, pick a default model, and every agent can use it immediately — or add Poe as one engine among several and let tasks route to the best fit.

Featured models

Model Context Reasoning Released
Claude-Opus-4.8 1M Yes 2026-05-28
Gemini-3.5-Flash 1M Yes 2026-05-19
DeepSeek-V4-Flash-EL 1M Yes 2026-04-24
DeepSeek-V4-Pro-EL 1M Yes 2026-04-24
GPT-Image-2 — No 2026-04-21
Kimi-K2.6 262K Yes 2026-04-20

How it works

01

Connect

In WorkDaddy, open Settings → Models, choose Poe, and paste your API key (POE_API_KEY). No key? Start on the managed gateway instead.

02

Put agents to work

Pick Claude-Opus-4.8 or any of the 137 available models as your default — per-agent overrides let you match model to task.

03

Review and approve

Agent output stays draft-first regardless of the model: review diffs and approve actions exactly as before.

Frequently asked questions

Does WorkDaddy support Poe in 2026?

Yes — Poe is a supported LLM provider with 137 models in the WorkDaddy catalog, connected with your own API key via the @ai-sdk/openai-compatible adapter.

How many Poe models can I use with WorkDaddy?

137 models are listed for Poe, including 71 reasoning models and 94 vision-capable models. The flagship lineup above shows the newest.

What context window do Poe models offer?

Up to 2M tokens on the largest model — relevant for whole-repo storefront work and long analytics reports.

Is Poe the best LLM provider for e-commerce agents?

It depends on the task mix — Poe sits in the Aggregators & Gateways group. WorkDaddy is model-agnostic, so the practical answer in 2026 is to combine providers: route each agent task to whichever model fits best.

Put the team to work on your store

Connect your storefront, analytics, and email stack, set a goal, and let the agents run the work end to end. Start on the free plan with your own model key.