Musah Abdulai
@musabdulai.com
https://musabdulai.com | I design & build secure, RAG-first AI systems for B2B teams—with security, privacy, reliability & DevOps.
Talk to me: 𝐡𝐞𝐥𝐥𝐨@𝐦𝐮𝐬𝐚𝐛𝐝𝐮𝐥𝐚𝐢.𝐜𝐨𝐦
Talk to me: 𝐡𝐞𝐥𝐥𝐨@𝐦𝐮𝐬𝐚𝐛𝐝𝐮𝐥𝐚𝐢.𝐜𝐨𝐦
The most expensive tokens in your RAG system aren’t the ones you send.
They’re the ones that:
• Hit sensitive docs
• Bypass weak filters
• End up screenshotted into Slack forever
Data minimization is a cost control.
They’re the ones that:
• Hit sensitive docs
• Bypass weak filters
• End up screenshotted into Slack forever
Data minimization is a cost control.
December 10, 2025 at 2:35 PM
The most expensive tokens in your RAG system aren’t the ones you send.
They’re the ones that:
• Hit sensitive docs
• Bypass weak filters
• End up screenshotted into Slack forever
Data minimization is a cost control.
They’re the ones that:
• Hit sensitive docs
• Bypass weak filters
• End up screenshotted into Slack forever
Data minimization is a cost control.
Before you optimize RAG latency from 1.2s → 0.8s, ask:
• Do we know our top 10 expensive users?
• Do we know which indexes drive 80% of cost?
• Do we know our riskiest collections?
Performance tuning without cost & risk data is vibes-based engineering.
• Do we know our top 10 expensive users?
• Do we know which indexes drive 80% of cost?
• Do we know our riskiest collections?
Performance tuning without cost & risk data is vibes-based engineering.
December 9, 2025 at 4:12 PM
Before you optimize RAG latency from 1.2s → 0.8s, ask:
• Do we know our top 10 expensive users?
• Do we know which indexes drive 80% of cost?
• Do we know our riskiest collections?
Performance tuning without cost & risk data is vibes-based engineering.
• Do we know our top 10 expensive users?
• Do we know which indexes drive 80% of cost?
• Do we know our riskiest collections?
Performance tuning without cost & risk data is vibes-based engineering.
Your vector DB is now:
• A data warehouse
• A search engine
• An attack surface
• A cost center
Still treating it like a sidecar for “chat with your docs” is how you get surprise invoices and surprise incidents.
• A data warehouse
• A search engine
• An attack surface
• A cost center
Still treating it like a sidecar for “chat with your docs” is how you get surprise invoices and surprise incidents.
December 9, 2025 at 8:33 AM
Your vector DB is now:
• A data warehouse
• A search engine
• An attack surface
• A cost center
Still treating it like a sidecar for “chat with your docs” is how you get surprise invoices and surprise incidents.
• A data warehouse
• A search engine
• An attack surface
• A cost center
Still treating it like a sidecar for “chat with your docs” is how you get surprise invoices and surprise incidents.
Hot take:
“Guardrails” are often a guilt-offload for not doing:
• Proper access control
• Per-tenant isolation
• Input/output logging
LLM wrappers won’t fix a broken security model. They just make it more expensive.
“Guardrails” are often a guilt-offload for not doing:
• Proper access control
• Per-tenant isolation
• Input/output logging
LLM wrappers won’t fix a broken security model. They just make it more expensive.
December 8, 2025 at 2:05 PM
Hot take:
“Guardrails” are often a guilt-offload for not doing:
• Proper access control
• Per-tenant isolation
• Input/output logging
LLM wrappers won’t fix a broken security model. They just make it more expensive.
“Guardrails” are often a guilt-offload for not doing:
• Proper access control
• Per-tenant isolation
• Input/output logging
LLM wrappers won’t fix a broken security model. They just make it more expensive.
Hidden RAG cost center: abuse.
• No per-user rate limits
• Unlimited queries on expensive models
• Tool calls that hit paid APIs
Congrats, you just built a token-minter for attackers.
Security is also about protecting your wallet.
• No per-user rate limits
• Unlimited queries on expensive models
• Tool calls that hit paid APIs
Congrats, you just built a token-minter for attackers.
Security is also about protecting your wallet.
December 7, 2025 at 2:32 PM
Hidden RAG cost center: abuse.
• No per-user rate limits
• Unlimited queries on expensive models
• Tool calls that hit paid APIs
Congrats, you just built a token-minter for attackers.
Security is also about protecting your wallet.
• No per-user rate limits
• Unlimited queries on expensive models
• Tool calls that hit paid APIs
Congrats, you just built a token-minter for attackers.
Security is also about protecting your wallet.
Observability for RAG isn’t just “for quality”:
• Track token spend per user/tenant
• Track which collections are most queried
• Track which prompts hit sensitive docs
Same logs help with cost optimization AND security forensics. Double win.
• Track token spend per user/tenant
• Track which collections are most queried
• Track which prompts hit sensitive docs
Same logs help with cost optimization AND security forensics. Double win.
December 7, 2025 at 2:32 PM
Observability for RAG isn’t just “for quality”:
• Track token spend per user/tenant
• Track which collections are most queried
• Track which prompts hit sensitive docs
Same logs help with cost optimization AND security forensics. Double win.
• Track token spend per user/tenant
• Track which collections are most queried
• Track which prompts hit sensitive docs
Same logs help with cost optimization AND security forensics. Double win.
Every “just in case” token you send has a cost:
• Direct $$
• Latency
• Attack surface
Prune your retrieval:
• Fewer, higher-quality chunks
• Explicit collections
• Permission-aware filters
Spend less, answer faster, leak less.
• Direct $$
• Latency
• Attack surface
Prune your retrieval:
• Fewer, higher-quality chunks
• Explicit collections
• Permission-aware filters
Spend less, answer faster, leak less.
December 6, 2025 at 3:03 PM
Every “just in case” token you send has a cost:
• Direct $$
• Latency
• Attack surface
Prune your retrieval:
• Fewer, higher-quality chunks
• Explicit collections
• Permission-aware filters
Spend less, answer faster, leak less.
• Direct $$
• Latency
• Attack surface
Prune your retrieval:
• Fewer, higher-quality chunks
• Explicit collections
• Permission-aware filters
Spend less, answer faster, leak less.
Your RAG threat model should include finance:
• Prompt injection that triggers many tool calls
• Queries crafted to hit max tokens every time
• Abuse of “unlimited internal use” policies
Attackers don’t need your data if they can just drain your budget.
• Prompt injection that triggers many tool calls
• Queries crafted to hit max tokens every time
• Abuse of “unlimited internal use” policies
Attackers don’t need your data if they can just drain your budget.
December 6, 2025 at 2:57 PM
Your RAG threat model should include finance:
• Prompt injection that triggers many tool calls
• Queries crafted to hit max tokens every time
• Abuse of “unlimited internal use” policies
Attackers don’t need your data if they can just drain your budget.
• Prompt injection that triggers many tool calls
• Queries crafted to hit max tokens every time
• Abuse of “unlimited internal use” policies
Attackers don’t need your data if they can just drain your budget.
RAG tradeoff triangle:
• More context → more tokens
• Less context → more hallucinations
• No security → more incidents
Most teams only tune the first two.
Mature teams treat security as a cost dimension too.
• More context → more tokens
• Less context → more hallucinations
• No security → more incidents
Most teams only tune the first two.
Mature teams treat security as a cost dimension too.
December 5, 2025 at 2:31 PM
RAG tradeoff triangle:
• More context → more tokens
• Less context → more hallucinations
• No security → more incidents
Most teams only tune the first two.
Mature teams treat security as a cost dimension too.
• More context → more tokens
• Less context → more hallucinations
• No security → more incidents
Most teams only tune the first two.
Mature teams treat security as a cost dimension too.
“Low token cost” demos lie.
In real life RAG:
• 20–50 retrieved chunks
• Tool calls
• Follow-up questions
Now add:
• No rate limits
• No abuse detection
• No guardrails on tools
Congrats, you’ve built a DoS and data-exfil API with pretty UX.
In real life RAG:
• 20–50 retrieved chunks
• Tool calls
• Follow-up questions
Now add:
• No rate limits
• No abuse detection
• No guardrails on tools
Congrats, you’ve built a DoS and data-exfil API with pretty UX.
December 5, 2025 at 8:51 AM
“Low token cost” demos lie.
In real life RAG:
• 20–50 retrieved chunks
• Tool calls
• Follow-up questions
Now add:
• No rate limits
• No abuse detection
• No guardrails on tools
Congrats, you’ve built a DoS and data-exfil API with pretty UX.
In real life RAG:
• 20–50 retrieved chunks
• Tool calls
• Follow-up questions
Now add:
• No rate limits
• No abuse detection
• No guardrails on tools
Congrats, you’ve built a DoS and data-exfil API with pretty UX.
RAG security checklist nobody wants to do:
☐ Can the model see secrets in your vector DB?
☐ Can users pivot across tenants via “helpful” answers?
☐ Are tool calls rate-limited & logged?
☐ Are prompts & retrieved docs auditable?
If the answer is “we’re moving fast”, the real answer is “no”.
☐ Can the model see secrets in your vector DB?
☐ Can users pivot across tenants via “helpful” answers?
☐ Are tool calls rate-limited & logged?
☐ Are prompts & retrieved docs auditable?
If the answer is “we’re moving fast”, the real answer is “no”.
December 4, 2025 at 8:05 PM
RAG security checklist nobody wants to do:
☐ Can the model see secrets in your vector DB?
☐ Can users pivot across tenants via “helpful” answers?
☐ Are tool calls rate-limited & logged?
☐ Are prompts & retrieved docs auditable?
If the answer is “we’re moving fast”, the real answer is “no”.
☐ Can the model see secrets in your vector DB?
☐ Can users pivot across tenants via “helpful” answers?
☐ Are tool calls rate-limited & logged?
☐ Are prompts & retrieved docs auditable?
If the answer is “we’re moving fast”, the real answer is “no”.
Token cost tip for RAG:
Security ≠ “retrieve everything, hope the model ignores the sensitive parts”.
• Use per-collection permissions
• Filter before retrieval, not after
• Keep PII-heavy docs in separate indices
Every token you don’t send is cheaper, faster, and safer.
Security ≠ “retrieve everything, hope the model ignores the sensitive parts”.
• Use per-collection permissions
• Filter before retrieval, not after
• Keep PII-heavy docs in separate indices
Every token you don’t send is cheaper, faster, and safer.
December 4, 2025 at 12:05 PM
Token cost tip for RAG:
Security ≠ “retrieve everything, hope the model ignores the sensitive parts”.
• Use per-collection permissions
• Filter before retrieval, not after
• Keep PII-heavy docs in separate indices
Every token you don’t send is cheaper, faster, and safer.
Security ≠ “retrieve everything, hope the model ignores the sensitive parts”.
• Use per-collection permissions
• Filter before retrieval, not after
• Keep PII-heavy docs in separate indices
Every token you don’t send is cheaper, faster, and safer.
RAG maturity levels:
0️⃣ “Just add RAG, ship the demo.”
1️⃣ “We optimize token cost and relevance.”
2️⃣ “We have per-tenant indexes and basic auth.”
3️⃣ “We treat RAG as an application security problem: threat model, least privilege, audits, and incident response.”
Most teams are stuck at 1.5.
0️⃣ “Just add RAG, ship the demo.”
1️⃣ “We optimize token cost and relevance.”
2️⃣ “We have per-tenant indexes and basic auth.”
3️⃣ “We treat RAG as an application security problem: threat model, least privilege, audits, and incident response.”
Most teams are stuck at 1.5.
December 4, 2025 at 11:31 AM
RAG maturity levels:
0️⃣ “Just add RAG, ship the demo.”
1️⃣ “We optimize token cost and relevance.”
2️⃣ “We have per-tenant indexes and basic auth.”
3️⃣ “We treat RAG as an application security problem: threat model, least privilege, audits, and incident response.”
Most teams are stuck at 1.5.
0️⃣ “Just add RAG, ship the demo.”
1️⃣ “We optimize token cost and relevance.”
2️⃣ “We have per-tenant indexes and basic auth.”
3️⃣ “We treat RAG as an application security problem: threat model, least privilege, audits, and incident response.”
Most teams are stuck at 1.5.
If your RAG system:
– Reads from prod data
– Writes to prod systems
– Has no formal threat model
…that’s not “experimentation”.
That’s shadow production with a chatbot UI.
Security, logging, and rollback matter more when the behavior is probabilistic.
– Reads from prod data
– Writes to prod systems
– Has no formal threat model
…that’s not “experimentation”.
That’s shadow production with a chatbot UI.
Security, logging, and rollback matter more when the behavior is probabilistic.
December 3, 2025 at 10:51 AM
If your RAG system:
– Reads from prod data
– Writes to prod systems
– Has no formal threat model
…that’s not “experimentation”.
That’s shadow production with a chatbot UI.
Security, logging, and rollback matter more when the behavior is probabilistic.
– Reads from prod data
– Writes to prod systems
– Has no formal threat model
…that’s not “experimentation”.
That’s shadow production with a chatbot UI.
Security, logging, and rollback matter more when the behavior is probabilistic.
Hot take: “Just add RAG” quietly created the biggest new security perimeter in years.
• Prompt injection
• Data exfiltration via clever questions
• Over-permissive tools/actions
If your AI app touches customer data or prod, you don’t have a chatbot problem, you have an application security problem
• Prompt injection
• Data exfiltration via clever questions
• Over-permissive tools/actions
If your AI app touches customer data or prod, you don’t have a chatbot problem, you have an application security problem
December 2, 2025 at 2:50 PM
Hot take: “Just add RAG” quietly created the biggest new security perimeter in years.
• Prompt injection
• Data exfiltration via clever questions
• Over-permissive tools/actions
If your AI app touches customer data or prod, you don’t have a chatbot problem, you have an application security problem
• Prompt injection
• Data exfiltration via clever questions
• Over-permissive tools/actions
If your AI app touches customer data or prod, you don’t have a chatbot problem, you have an application security problem
If your RAG system trusts:
– Any website it scrapes
– Any PDF users upload
– Any internal wiki page
…then you’re 1 prompt-injection away from leaking secrets or executing bad actions.
“LLM security” = data provenance + least privilege + auditing, not just cooler guardrails.
– Any website it scrapes
– Any PDF users upload
– Any internal wiki page
…then you’re 1 prompt-injection away from leaking secrets or executing bad actions.
“LLM security” = data provenance + least privilege + auditing, not just cooler guardrails.
December 2, 2025 at 8:42 AM
If your RAG system trusts:
– Any website it scrapes
– Any PDF users upload
– Any internal wiki page
…then you’re 1 prompt-injection away from leaking secrets or executing bad actions.
“LLM security” = data provenance + least privilege + auditing, not just cooler guardrails.
– Any website it scrapes
– Any PDF users upload
– Any internal wiki page
…then you’re 1 prompt-injection away from leaking secrets or executing bad actions.
“LLM security” = data provenance + least privilege + auditing, not just cooler guardrails.
Most “RAG security” talk is about better prompts.
The real risk? Untrusted data → trusted answers.
If your RAG can:
• Read internal docs
• Call tools / APIs
• Write to prod systems
…then every data source is a potential remote code execution.
Treat retrieval as an attack surface, not a feature
The real risk? Untrusted data → trusted answers.
If your RAG can:
• Read internal docs
• Call tools / APIs
• Write to prod systems
…then every data source is a potential remote code execution.
Treat retrieval as an attack surface, not a feature
December 1, 2025 at 2:44 PM
Most “RAG security” talk is about better prompts.
The real risk? Untrusted data → trusted answers.
If your RAG can:
• Read internal docs
• Call tools / APIs
• Write to prod systems
…then every data source is a potential remote code execution.
Treat retrieval as an attack surface, not a feature
The real risk? Untrusted data → trusted answers.
If your RAG can:
• Read internal docs
• Call tools / APIs
• Write to prod systems
…then every data source is a potential remote code execution.
Treat retrieval as an attack surface, not a feature
Big drop in opens/replies?
Probably not your copy, it’s inbox placement.
I help B2B teams fix SPF/DKIM/DMARC, domain reputation + list hygiene in a 3-week Inbox Rescue Sprint.
Reply INBOX and I’ll tell you what I’d check on your domain.
Probably not your copy, it’s inbox placement.
I help B2B teams fix SPF/DKIM/DMARC, domain reputation + list hygiene in a 3-week Inbox Rescue Sprint.
Reply INBOX and I’ll tell you what I’d check on your domain.
November 28, 2025 at 7:52 PM
Big drop in opens/replies?
Probably not your copy, it’s inbox placement.
I help B2B teams fix SPF/DKIM/DMARC, domain reputation + list hygiene in a 3-week Inbox Rescue Sprint.
Reply INBOX and I’ll tell you what I’d check on your domain.
Probably not your copy, it’s inbox placement.
I help B2B teams fix SPF/DKIM/DMARC, domain reputation + list hygiene in a 3-week Inbox Rescue Sprint.
Reply INBOX and I’ll tell you what I’d check on your domain.
Automation isn’t about tools, it’s about turning decisions into rules. Define the rule, automate the repeat, free the team to build.
November 24, 2025 at 6:15 PM
Automation isn’t about tools, it’s about turning decisions into rules. Define the rule, automate the repeat, free the team to build.
A client missed their launch, not because they were slow, but because they spent the month fixing the same broken workflow.
When we mapped a single process, cleaned it up, and automated the repeats, the next quarter they hit their target with ease.
The real problem was never effort.
It was ops.
When we mapped a single process, cleaned it up, and automated the repeats, the next quarter they hit their target with ease.
The real problem was never effort.
It was ops.
November 24, 2025 at 6:08 PM
A client missed their launch, not because they were slow, but because they spent the month fixing the same broken workflow.
When we mapped a single process, cleaned it up, and automated the repeats, the next quarter they hit their target with ease.
The real problem was never effort.
It was ops.
When we mapped a single process, cleaned it up, and automated the repeats, the next quarter they hit their target with ease.
The real problem was never effort.
It was ops.
If your infrastructure can't survive one day without you checking it, you don't have infrastructure - you have a hobby that pays badly.
Build systems that work while you sleep, eat brunch, and ignore Slack.
Build systems that work while you sleep, eat brunch, and ignore Slack.
September 27, 2025 at 8:44 PM
If your infrastructure can't survive one day without you checking it, you don't have infrastructure - you have a hobby that pays badly.
Build systems that work while you sleep, eat brunch, and ignore Slack.
Build systems that work while you sleep, eat brunch, and ignore Slack.
Does anyone besides you know how to deploy the app?
If the answer is no, you don't have a deployment process - you have a single point of failure with a salary.
Document everything. #DevOps
If the answer is no, you don't have a deployment process - you have a single point of failure with a salary.
Document everything. #DevOps
September 26, 2025 at 4:21 PM
Does anyone besides you know how to deploy the app?
If the answer is no, you don't have a deployment process - you have a single point of failure with a salary.
Document everything. #DevOps
If the answer is no, you don't have a deployment process - you have a single point of failure with a salary.
Document everything. #DevOps
If your deploy process involves opening 5 different browser tabs and remembering a sequence of commands, you're one sick day away from breaking production.
Automate it. Document it. Make it boring.
#DevOps
Automate it. Document it. Make it boring.
#DevOps
September 26, 2025 at 7:45 AM
If your deploy process involves opening 5 different browser tabs and remembering a sequence of commands, you're one sick day away from breaking production.
Automate it. Document it. Make it boring.
#DevOps
Automate it. Document it. Make it boring.
#DevOps
Just earned a Google Cloud badge in CI/CD & automation.
Quick checklist:
1) Gate merges with fast automated tests to stop regressions;
2) Deploy small canaries + automated health checks to catch issues early. www.credly.com/badges/2c79c... via @credly @GoogleCloudTech #CICD
Quick checklist:
1) Gate merges with fast automated tests to stop regressions;
2) Deploy small canaries + automated health checks to catch issues early. www.credly.com/badges/2c79c... via @credly @GoogleCloudTech #CICD
Implement DevOps Workflows in Google Cloud Skill Badge was issued by Google Cloud to Abdulai Musah.
Complete the Implement DevOps Workflows in Google Cloud skill badge to demonstrate skills in the following: creating git repositories with Cloud Source Repositories, launching, managing, and scaling d...
www.credly.com
September 26, 2025 at 7:43 AM
Just earned a Google Cloud badge in CI/CD & automation.
Quick checklist:
1) Gate merges with fast automated tests to stop regressions;
2) Deploy small canaries + automated health checks to catch issues early. www.credly.com/badges/2c79c... via @credly @GoogleCloudTech #CICD
Quick checklist:
1) Gate merges with fast automated tests to stop regressions;
2) Deploy small canaries + automated health checks to catch issues early. www.credly.com/badges/2c79c... via @credly @GoogleCloudTech #CICD
Your biggest vulnerability isn't hackers. It's that one team member who has the production database password saved in their browser and no one else knows it.Document your infrastructure. Share credentials properly. Bus factor of one is a ticking time bomb.
July 25, 2025 at 11:29 PM
Your biggest vulnerability isn't hackers. It's that one team member who has the production database password saved in their browser and no one else knows it.Document your infrastructure. Share credentials properly. Bus factor of one is a ticking time bomb.